data science phd programs in california

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Data Science Degree Programs in California

Created by aasif.faizal

If you’re pursuing a career in the booming field of data science and are ready to relocate, you might want to consider making your way to the Golden State.

California is the center of the data science world.

The state is home to the world’s fastest growing tech startups and most innovative companies. Google, Apple, and Facebook are just a few of the juggernauts with huge operations in California. These companies drive significant demand for computer science, software engineering, and data science professionals.

California schools supply much of the talent that pushes these powerhouses forward. Between the University of California system and other prestigious schools, an incredible amount of investment goes into developing effective educational programs and research initiatives.

For example, some of the biggest universities in the state have been labeled by the NIH as Centers of Excellence for Big Data Computing. UC Berkeley currently plays a big part in a near $40 million Data-Driven Discovery Initiative that aims to build tools and sophistication around data science tools and techniques. The National Science Foundation has partnered with several major California universities to set up Industry / University Cooperative Research Centers. At a high level, the state is constantly buzzing with data science-related activity.

For current California-based data science professionals, there is no shortage of relevant groups or communities to join. San Francisco’s longest-running meetup, SF Data Mining, includes more than 10,000 members and features frequent conversations around data science and big data. Big Data Science out of Fremont is an organization that has been organizing webinars and meetups for data science professionals since 2012. No matter the niche focus or location, there is something for everyone in California.

Many of the world’s largest data science conferences also go through the state.

• Every November, MLconf San Francisco features speakers from major corporations who discuss the importance of machine learning and data science in the business setting.
• In San Diego, the Data Science Innovation Summit welcomes leaders from major tech companies all throughout the state and encourages them to network with one another.
• Stanford hosts Women in Data Science, a one-day technical conference that typically sees 400 attendees from 110 companies and universities.

Upon graduation, there are endless opportunities to remain engaged with the broader data science community.

Given its positioning in the realm of data science, it’s no surprise that California schools were among the first to offer advanced study in the field.

Today, more than 25 universities offer Masters of Data Science programs and new undergraduate programs are being launched every year.

Career Outlook for Data Scientists in California

According to the Bureau of Labor Statistics , California has the highest concentration of data scientists, employing 17,750 workers in the field statewide. This should come as no surprise given that the state is home to so many major tech companies.

If this sounds like good news, it only gets better: the Bureau of Labor Statistics anticipates a job growth rate of 36% for data scientists by 2031, with 13,500 new job openings anticipated for each new year. In other words, those concerned about job security can trust that data science is a reliable field to plot a career.

Also unsurprisingly, more than half of the top 20 institutions that feed data science talent to Silicon Valley companies are based in California. This shows that choosing a degree program in California can be beneficial to your career in the long term.

The Bureau of Labor Statistics also reports fantastic wages for California-based data scientists, with pay rates drastically exceeding the averages for the majority of other professions. The annual mean wage for data scientists in California is an impressive $133,110. Broken down hourly, this comes out to $64 an hour, considerably higher than many other occupations.

The state also boasts four of the top ten metropolitan areas in the country (listed below) for data science-related career opportunities.

San Jose / Sunnyvale / Santa Clara:

• Data science employment: 3,530
• Hourly mean wage: $75.53
• Annual mean wage: $157,110

The San Jose metropolitan area ranks first in the country on annual mean wage compared to all other metropolitan areas, according to the Bureau of Labor Statistics.

San Francisco / Redwood City / South San Francisco:

• Data science employment: 5,290
• Hourly mean wage: $73.65
• Annual mean wage: $153,180

The San Francisco metropolitan area ranks second in the country on annual mean wage compared to all other metropolitan areas, according to the Bureau of Labor Statistics.

Los Angeles / Long Beach / Glendale:

• Data science employment: 3,830
• Hourly mean wage: $57.33
• Annual mean wage: $119,240

According to the Bureau of Labor Statistics, the Los Angeles metropolitan area ranks tenth in the country on annual mean wage compared to all other metropolitan areas.

When considering applying for a data science program in California, it’s important to keep a few things in mind. First, California is very expensive. The state ranks only behind Hawaii and DC on the Cost of Living Index scale. You should normalize the higher wages paid in California to truly understand the value of a data science job in the state. Second, develop a clear vision for how you would use your data science degree as there is an abundance of opportunity in California. You want to make sure you enroll in a program that will open the right doors for you after you graduate. Third, explore what financial options you have available and try to mitigate some of the costs of a program. Fortunately, there is a lot of scholarship funding and financial aid available for students in California.

California Universities and Data Science Degree Programs: On-Campus Undergraduate, Graduate, Masters, and PhD

Twenty-five different universities in California offer a diversity of data science programs. Prospective students in the state have a plethora of options available all across the state, from on-campus undergraduate programs to remote master’s degrees. Graduate certificates are also a popular path in California as many students prefer to enroll in skills-focused courses that can help them sharpen their skills for real-world applications. Choosing the right path for yourself depends on your future goals and interests as a data science professional.

On-Campus Undergraduate Data Science Programs

Over the past several years, there has been a dramatic increase in the number of universities offering undergraduate data science programs. Behind this trend is the rise in analytical roles in the workforce that require skills in data manipulation and visualization.

California schools offer a number of undergraduate data science programs for prospective students. Prerequisites vary from school to school. However, it’s helpful to have a background in statistics or computer science when applying.

Mills College offers a major in data science with four specialization tracks covering sociological, economic, mathematical, and computational analytics. A minimum of 53 credits must be completed in order to earn the degree. You can also pursue a one-year master’s in computer science or applied economics if you work closely with an advisor to optimize your curriculum.

The University of California Irvine’s data science degree program includes a capstone project and covers many areas, including machine learning, Bayesian statistics, and computer science. You must complete 135 credits in order to earn the degree.

On-Campus Graduate Data Science Programs

There are many on-campus and online graduate data science programs all across the state.

Students can earn graduate certificates or degrees in the field that are extremely valuable and immediately useful.

The California State University and University of California school systems both offer many options. However, if you prefer smaller institutions, there are also numerous high-quality programs available at private universities.

On-Campus Master’s in Data Science Programs

Stanford, USC, and the University of California San Diego offer three of the best master’s programs in the country in data science. Outside of these schools, there are plenty of alternatives that provide different course designs and areas of concentration.

Stanford’s MS in Statistics Data Science program is a 45-credit track that can be completed in 2 years. No thesis is required in order to complete the program and students are exposed to a wide array of topics, including statistical modeling, data mining, and discrete mathematics.

Furthermore, if you’d prefer Southern California living, USC offers a 32-unit Master of Science in Computer Science program that covers various fields, such as artificial intelligence, database systems, and data analysis. The program costs $61,984 and can also be completed online.

On-Campus Data Science Ph.D Programs

When it comes to Ph.D. programs, California has a few data science-specific programs and several tangentially related programs.

At the USC Marshall School of Business, students can complete a 5-year Ph.D. in Data Sciences and Operations along one of two paths, operations management or statistics. Program completion requires at least 60 credits of coursework. Tuition is $114,720 total ($1,912 per hour). Full financial support is available for four to five years for selected students.

More specifically, Chapman University in Irvine, California offers a 70-credit Doctorate in Computational and Data Science program consisting of 13 core credits, 45 elective credits, and 12 dissertation research credits. Classes are delivered online and the program costs $109,550 ($1,565 per credit).

On-Campus Graduate Certificate Programs

If you are relatively new to data science and want to build a strong foundation of knowledge and skill in the field, a graduate certificate could be a great option.

Five different California schools offer graduate certificates for data science-related sub-specialties:

• CSU-Fullerton
• Humboldt State
• San Jose State University

Start your search with one of these schools to see which one offers the type of experience and focus you are seeking.

Also keep in mind that California is a large state with subcultures that vary as much as the geography. UC Irvine and Fullerton are located in sunny Southern California vs. Stanford and Humboldt State are much further north (Humboldt State is not far from the California and Oregon border).

Stanford is one of the private universities in California which dominates data science education. Stanford’s Data Mining and Applications program introduces students to predictive modeling and teaches statistical methods for working with large sets of data. Students must complete 10 units of coursework in under 3 years. The cost of tuition is $12,600. The more specific Mining Massive Data Sets Graduate Certificate program helps students master techniques for gleaning insights from extremely large datasets. Students must complete 15 units of coursework in under 3 years. Tuition for the certificate costs $18,900.

For those of you who are more interested in what Southern California schools have to offer, UC Irvine’s Data Science Certificate program consists of 15 units of coursework that can be completed in 9-15 months. Students must take an introductory data science course before choosing from a number of electives covering a wide range of topics, including data modeling, Python, and Hadoop. The average cost of the program is $4,795.

Online Data Science Degree Programs in California

Although there are fewer online data science master’s programs than graduate certificate programs, there are still a number of options available across the state. Universities, such as UC Berkeley and UC Riverside, have been offering online programs for several years.

As you explore online data science degree programs in California, consider what specific area of concentration you are most interested in, as well as what your career goals are. Data science and data engineering are intertwined, but they are different daily functions (e.g., building data pipelines, database architecture, maintaining the health of data processing systems, is the domain of the data engineer).

UC Berkeley offers a flexible and multidisciplinary 27-unit online Master of Information and Data Science program. You can complete the program on an accelerated timeline or on a part-time basis. Additionally, you must complete a capstone project. Berkeley’s online MIDS program costs $62,991. Fortunately, the university offers many graduate fellowships to help reduce some of the cost burden on students.

Data scientists who would intend on adding data engineering knowledge and skills to their repertoire may be interested in UCLA’s 36-unit data science engineering program. You’ll be required to complete a capstone project or pass three written exams. The program typically takes 2.25 years to complete and costs $36,000 ($4,000 per course). A GRE is required in order to be accepted.

Best Data Science Programs in California

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» Ph.D. in Computational and Data Sciences

Computational Science is the art of creating, developing, and validating models in order to gain a profound understanding of real-life complex problems. Data Science is the art of generating insight, knowledge, and predictions by applying modern methods to large datasets.  

In Chapman University’s Ph.D. in Computational and Data Sciences program, you will collaborate on innovative research as you work closely with   nationally and internationally renowned   faculty mentors who will help prepare you to thrive in a variety of professional settings, from academia to private industry, scientific research labs to government agencies. You will learn to design and implement mathematical models and refine quantitative analysis techniques to solve complex scientific problems. Develop your dissertation with focus on advancement of theory and applications of statistical, machine learning and AI in diverse data science related fields such as medicine and epidemiology, climate and Earth hazards, big data and high-performance computing, drug design, genetics, natural language processing, bioinformatics and biotechnology, economics, and sports analytics. 

Employment and Future Opportunities

In our tech-driven world, employers are increasingly recognizing the value of data science professionals.  According to U.S. News and World Report, the Bureau of Labor Statistics projects 35.8% employment growth for data scientists between 2021 and 2031. In this period, an estimated 40,500 jobs should open up.  

Graduates from the program have gone on to work in a variety of industries, such as:  

• Artificial Intelligence and Machine Learning 
• Higher Education Institutions 
• Healthcare 
• Entertainment Industry 
• Government Agencies 
• Large Tech Companies such as Amazon, Microsoft, Google, Yahoo 

Ph.D. Student Handbook

For the latest information on the current curriculum, please visit the Graduate Catalog .

Prerequisites

It is expected that students admitted to the CADS Ph.D. program will have completed substantial preparatory coursework as an undergraduate major or minor from a regionally accredited institution in one of the following disciplines, or the equivalent: Mathematics, Statistics, Computer Science, Data Science, Physics, Electrical Engineering, or Software Engineering.

Preparatory coursework must include the following courses, or the equivalent:

• Linear Algebra
• Multivariable Calculus
• Differential Equations
• Computer Programming: Data Structures preferred (R, Python, and SQL)
• Probability and Statistics (Distributions, Confidence Intervals, Hypothesis Testing, Linear Models)

Total Credits - 70

Admission Requirements

An undergraduate degree specifically in computational science is not required for admission. The program will consider applicants from a broad range of undergraduate and master’s level science disciplines (e.g. biology, chemistry, computer science, biochemistry and molecular biology, mathematics, physics). Admission will depend on the relationship between the student’s goals and the program’s objectives as well as the likelihood that the student will benefit from the program.

1 . Prerequisite Courses

2. Application Requirements

Admission to the program may be achieved by the completion of the following requirements:

Online application for admission (including $60 non-refundable application fee)

Official transcript from degree granting institution. If prerequisite courses have been taken at schools other than the degree granting institution, those transcripts must also be submitted. Applicants must have earned a minimum grade point average of 3.00.

Graduate Admission Test Scores (School Code: 4047); the Graduate Record Examination (GRE) general test scores must have been taken within the last five years. Applicants must achieve the following minimum scores:

• Verbal: 153
• Quantitative: 146
• Analytical Writing: 4.0

To request a GRE waiver, complete this form . Once you submit your waiver request, you will be notified by email in 1-2 weeks if the GRE has been waived for you. Each waiver is reviewed on a case-by-case basis.

Letters of recommendation - two letters of recommendation are required, including one from an academic source which describes your professional and academic abilities.

Statement of Intent - a 750 word essay; applicants are expected to address science topics they are interested in and how they envision applying computational science in those areas.

Resume - a resume or curriculum vitae is required

International student application requirements

Chapman's language of instruction is English. If you have not received a bachelor's degree (or higher) at an institute where English was the language of instruction, you must demonstrate English proficiency by submitting official scores from an English language exam. You can find additional information here .

Official Transcripts and Diploma

• Your application requires official transcripts in both the native language, and in English. If your university does not provide translations of your transcript, you will need to have your transcript translated, line-by-line and word-for-word exactly. You will need to submit both the official transcript and the official translation.
• If your university only provides one official transcript, you will need to submit a notarized copy. You will need to take your official transcript and have certified copies made, and translated into English if needed. These documents should be stamped by the legal notary who made the copy and/or translation. We do not accept uncertified copies directly from students. Please note that official documents will be required upon acceptance.
• While your diploma will not be required with your application, your enrollment into Chapman University will be dependent upon submission of your official diploma. Should you be admitted, your diploma will need to be submitted in both the native language, and in English. You will need to submit both the official diploma and the official translation. If your university only provides one official diploma, you may send a notarized copy, or bring the original documents into our office at the time classes begin. 

Supplemental Application

• The International Supplemental Application is the financial certification form that provides comprehensive information about your passport, I-20 requirements, and financial support for your studies. This form is required for F-1 student visa applicants.
• Should you be admitted into our program, you will be sent information on how to access the Supplemental Application.
• If you hold a U.S. passport, or are a permanent resident, you do not need to submit this document. You will apply as a domestic student.

Tuition Information

Financial assistance is available in the form of federal loans, department scholarships, teaching assistantships, and research assistantships.

More information can be found on the Financial Aid website or by contacting Graduate Financial Aid at [email protected]  or (714) 628-2730.

Admission – Please contact the Associate Director of International Initiatives, DSO, Monica Chen, MA, at [email protected]  regarding your application, to schedule a campus visit or for other non-program specific questions.

Application : How to Apply

International Students – View our international student admissions page for additional information regarding applying to Chapman.

Tuition - Contact Student Business Services at (714) 997-6617 for information regarding tuition, fees, billing & payments. Please note that program staff are prohibited from discussing financial information.

Federal Financial Aid - For more information, email [email protected]  or call (714) 628-2730.

Housing - For graduate student housing options, contact Housing and Residence Life at (714) 997-6603.

Cyril Rakovski, Ph.D. Co-Program Director and Associate Professor

Areas of Research: Statistical modeling, Time Series Analysis, Bayesian

Mohamed Allali, Ph.D. Associate Professor

Areas of Research: Mathematical Modeling, Image Processing, Signal Processing

Daniel Alpay, Ph.D. Professor

Areas of Research: Schur Analysis; Slice-Hyperholomorphic functions; Signal Processing; Linear Systems; Wavelet Filters; White Noise Space

Vincent Berardi, Ph.D. Assistant Professor

Areas of Research: Computational Health Psychology, Behavioral Science, Mathematics, and Computational Science.

Peter Jipsen, Ph.D. Professor

Areas of Research: Universal Algebra; Lattice Theory; Residuated Lattices; Algebraic Logic; Substructural logics; enumerative combinatorics

Erik Linstead, Ph.D. Associate Professor

Areas of Research: Machine Learning; GPU Programming; Autism Spectrum Disorder; Assistive Technologies; Predictive Analytics; Virtual Reality

Uri Maoz, Ph.D. Assistant Professor

Areas of Research: Computational Neuroscience, Brain and Behavioral Sciences, Neural computation

Andrew Moshier, Ph.D. Professor

Areas of Research: Computation, Algebra & Topology

David Porter, Ph.D. Professor

Areas of Research: Economics and Mathematics, Testing and implementing new and complex market systems

Data Sciences + Operations PhD Program

Operations Management studies how firms organize their resources and recurring activities in order to be competitive in cost, price, responsiveness and quality. The field stresses quantitative techniques ranging from applied probability to optimization and game theory.

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• ADMISSIONS EVENTS

Operations Management

Operations Management studies how firms organize their resources and recurring activities in order to be competitive in cost, price, responsiveness and quality. The field stresses quantitative techniques ranging from applied probability to optimization and game theory. Successful applicants will have strong technical and mathematical training, and we particularly encourage applicants with undergraduate degrees in mathematics, economics and/or engineering to apply at the USC Application Portal. A prior background in business is not required.

Research areas: Our faculty are interested in a wide variety of research questions; check their personal webpages for specific examples. Some indicative topics include:

• Revenue management and dynamic pricing
• Data-driven analytics
• Healthcare operations
• Market and auction design
• Sustainability
• Supply-chain and service management

Operations Management and operations research prize interdisciplinary thinking and approaches. Hence, high-quality research often leverages a range of methodologies and tools, including:

• Optimization (linear, nonlinear, combinatorial, data-driven)
• Game Theory
• Queuing Theory
• Stochastic Processes / Applied Probability
• Econometrics
• Machine Learning

High quality research can involve developing new theoretical tools in these areas, application driven case studies, or both.

Our statistics faculty are interested in both pushing the boundaries of theoretical knowledge in the field as well as applied areas. There are many interesting research projects at the intersection of statistics, computer science, econometrics, finance, and marketing. Selected topics include:

• Statistical machine learning
• High­dimensional data analysis
• Computational and statistical limits of "Big data" problems
• Structural learning (such as clustering, sparse recovery and network analysis)
• Multiple hypotheses testing, uncertainty assessment and inference problems
• Finance and econometrics
• Applications in genetics, neuroscience and health care

Cutting­edge research in these areas leverages and builds upon many mathematical tools including:

• Functional data analysis
• Graphical models and iterative algorithms
• Optimization

Collegial, Supportive and Expansive

The DSO Ph.D. program is research-focused, collegial, supportive and highly interactive. Ph.D. students are viewed as “junior colleagues” and are encouraged to become involved in academic research with faculty early in their doctoral studies through the following programs and initiatives:

• Low student-to-faculty ratio coupled with the faculty's "open-door" policy leading to frequent and meaningful collaborations. Unlike many other PhD programs, successful students often collaborate with several different faculty members, both in operations and statistics, throughout their PhD. Successful students typically co-author several papers with faculty members, which are often published in top peer-reviewed journals in the field.
• Presentations by invited faculty from around the world as part of a regular seminar provide an opportunity for students to experience the breadth of the field and meet renowned scholars. Click here for more information.
• Internal brown-bag seminars and colloquia with other research-oriented universities in Southern California

Operations Management Research

Research Environment

The structure of the Ph.D. program permits great flexibility, allowing custom-tailored courses of study emphasizing all areas of specialization within the department. In addition to our own faculty, students typically draw on the distinguished faculty and outstanding resources available throughout the University, most notably in economics, mathematics, industrial and systems engineering, computer science, and the Information Sciences Institute. The Center for Global Supply Chain Management(GSCM) and the Institute for Communication Technology Management (CTM) are also key resources to this program.

Recognized Research Authorities

The Operations Management faculty have served as senior editors and associate editors of premier management journals, including:

• Management Science
• Manufacturing and Service Operations Management
• Naval Research and Logistics
• Operations Research
• Production and Operations Management

Faculty Honors

• Fellows, Production and Operations Management Society
• National Science Foundation Grants

Learn More:   Explore the Data Sciences and Operations department to learn more about current research and faculty activities.

Statistic Research

Research by the statistics faculty emphasizes developing new methodology that grows out of business and public policy applications. In methodology, the statistics faculty's research covers a wide segment of the field of statistics including Bayes and empirical Bayes methods, data mining, categorical data, hidden state Markov models, classification rules, clustering methods, econometric and psychometric models, and general linear models. Applications include finance, marketing, real estate, health policy, defense system testing, computer science and discrimination in employment and in sentencing.

The Statistics faculty members are among the leading authorities of Business Statistics worldwide. One senior Statistics faculty member plays a leading role in the profession's advice to the federal government on statistical methodology. In addition, Statistics faculty members have served as senior editors and associate editors of premier management journals, including:

• Annals of Statistics
• Journal of the American Statistical Association
• The Econometrics Journal
• Journal of Multivariate Analysis
• Statistica Sinica
• Fellow of the American Statistical Association; Noether Young Scholar Award; National Science Foundation Grants; National Science Foundation CAREER Award

Learn More:   Explore the Statistics group to learn more about current research and faculty activities.

Faculty Coordinator:   Vishal Gupta , Associate Professor of DSO

OPERATIONS MANAGEMENT REQUIREMENTS

Sample Course Schedule

• DSO 671: Inventory Models and Supply Chain Management
• GSBA 602: Selected Issues in Economic Theory
• ISE 631: Linear Programming
• Elective (1)
• ISE 538: Elements of Stochastic Processes (or MATH 505B: Applied Probability)
• DSO 677: Dynamic Programming and Markov Decision Processes
• ISE 630: Foundations of Optimization
• GSBA 604: Regression and Generalized Linear Models for Business
• BUCO 634: Communication for Doctoral Students: Conference Papers and Presentations
• Summer Research Paper

Research Development Beginning in the first semester, students will apprentice with a faculty mentor to learn research fundamentals. Typically students are assigned to a new mentor each semester in the first year. During the summer following the first year in the program, students are expected to research and complete a Summer Research Paper.

Screening Examination In addition to the papers and examinations assigned in their first-year courses, a screening process will occur in May at the end of the first year. This process will include a review of each student's grades, an analysis of competence in written communications and a written exam based on the material covered during the first year. The results of the examination help the faculty determine students’ developmental needs and fitness to continue in the program.

• DSO 670: Current Research in Operations management
• 3 electives
• DSO 674: Queuing and Stochastic Networks
• ISE 632: Metwork Flows and Combinatorial Optimization
• 2 electives
• BUCO 633: Communication for Doctoral Students: Foundations of Academic Writing
• BUCO 637: Communication for Doctoral Students: Succeeding as a Teacher
• Independent Dissertation Preparation (2)

Research Development At this stage in the program, the relationships Ph.D. candidates have developed through the research apprentices often lead to collaborative research projects. Ph.D. candidates continue to apprentice faculty with increasing responsibility. They also begin work on their dissertations and are expected to have an approved dissertation proposal before the start of the fourth year.

Teaching Development Ph.D. candidates begin developing teaching skills by serving as a teaching assistant for one or two classes and engaging in teaching skills workshops.

Qualifying Exam The examination qualifying a student for candidacy for the Ph.D. degree is partly written and partly oral, designed, at least in part, to test the student’s fitness to undertake independent research. After successful completion of the qualifying exams, the student is admitted to candidacy.

Research Development Research is the primary activity in the fourth year and beyond. Faculty view Ph.D. candidates as “junior colleagues” and partner to write and present papers.

Teaching Development Ph.D. candidates co-teach one course with a faculty member.

Dissertation Defense & Submission The dissertation is the culminating work of a student’s independent research. In the fourth or fifth year of the program, students complete, defend and submit the dissertation. This is the last step to earn the Ph.D. degree.

STATISTICS REQUIREMENTS

• MATH 541B Introduction to Mathematical Statistics
• ISE 630 Foundations of Optimization
• MATH 507A Theory of Probability or MATH 505a Applied Probability
• MATH 505b Applied Probability or Math 506 Stochastic Processes
• DSO 607 High-Dimensional Statistics and Big Data Problems
• GSBA 604 Regression and Generalized Linear Models for Business
• MATH 541A Introduction to Mathematical Statistics 1 elective

Research Development Beginning in the first semester, students will apprentice with a faculty mentor to learn research fundamentals. Typically students are assigned to a new mentor each semester in the first year. In the summer following the first year in the program, students research and complete a Summer Research Paper.

• MATH 541B Introduction to Mathematical Statistics or MATH 547 Methods of Statistical Inference (if already taken 541B)
• 3 electives (including a graduate level class in a selected business area)
• DSO 599 Special Topics Class

Research Development At this stage in the program, the relationships Ph.D. candidates have developed through the research apprentices often lead to collaborative research projects. Ph.D. candidates continue to apprentice faculty with increasing responsibility. They also begin work on their dissertations.

Qualifying Exam Students are required to complete the qualifying exam by November 1 of their third year. The examination qualifying a student for candidacy for the Ph.D. degree is partly written and partly oral, designed, at least in part, to test the student’s fitness to undertake independent research. After successful completion of the qualifying exams, the student is admitted to candidacy.

The department maintains a highly supportive and collegial atmosphere that fosters close cooperation and coordination among the faculty to ensure the integration of the several specific disciplines represented by individual members of the group. This collaborative imperative guarantees the continued relevance and timeliness of the teaching and research programs.

Student Background: Our students come from all of over the world. They have strong academic backgrounds and bring with them a variety of experiences prior to joining the program.

Rashmi Ranjan Bhuyan

• PhD Candidate in Data Sciences and Operations

Rashmi is a fourth year Ph.D. student in the statistics group at USC Marshall School of Business. He is broadly interested in machine learning and it's application in social science and business.

Sebnem Manolya Demir

• PhD Student in Data Sciences and Operations

Katerina Giannoutsou

Katerina Giannoutsou is a PhD student in the Data Sciences and Operations department in the Marshall School of Business. She previously obtained her bachelor’s degree in Mathematics and Economics at New York University and worked as a Research Assistant at the Operations Research Center of MIT where she focused on healthcare operations. Her current research focuses in mechanism design and the dynamics of two-sided platforms.

Sang-Wook Lee

Second year Ph.D. student in Data Sciences and Operations at USC Marshall School of Business

APPLYING TO THE PhD PROGRAM

Dates + deadlines.

December 15, 2023: Application Deadline - Accounting, Data Sciences & Operations, and Management & Organization* 

January 15, 2024: Application Deadline - Finance & Business Economics and Marketing 

The link to the PhD Program application is available on the Admissions page and the next opportunity to apply is for Fall 2024 admission. Late applications may or may not be considered at the discretion of the admissions committee. 

Admissions decisions are made from mid-February to mid-April. You will be notified by email when a decision has been made.

ADMISSIONS CONTACT

Ph.D. Program USC Marshall School of Business 3670 Trousdale Parkway, BRI 306 Los Angeles, California 90089-0809 EMAIL

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Graduate Education

Berkeley offers a variety of opportunities for graduate students, including master's programs and PhD programs with interdisciplinary designated emphases in data science.

Computational Biology

Ph.D. in Computational Biology

The main objective of the Computational Biology Ph.D. is to train the next generation of scientists who are passionate about exploring the interface of computation and biology and committed to functioning at a high level in both computational and biological fields.

Designated Emphasis in Computational and Genomic Biology

The Designated Emphasis is a specialization offered adjunct to affiliated doctoral degrees for students with research interests in computational biology and genomics. DE students receive a solid foundation in the different facets of computational/genomic research and the ensuing competitive edge for the most desirable jobs in academia and industry, which increasingly require interdisciplinary training.

Computational Precision Health

Ph.D. in Computational Precision Health

Students in the Ph.D. in Computational Precision Health develop skills and expertise in both the computational sciences (machine learning and AI, natural language processing, statistical inference and modeling, data standards, parallel computing and data at scale, etc.) and health sciences (clinical decision sciences and cognitive informatics, clinical delivery, clinical research, implementation science, health information policy, etc.).

Designated Emphasis in Computational Precision Health

Current UCSF and UC Berkeley PhD students from affiliated programs can incorporate CPH courses and advising into their Ph.D. Designated Emphasis students will receive a solid grounding in the fundamentals of computational precision health, with training in the application of computation to the practice of medicine and public health. 

Electrical Engineering and Computer Sciences

Master of Engineering (M.Eng.)

The Master of Engineering program offers innovative graduate courses on scientific and technical topics, organized by technical concentrations that match student interest.

Master of Science (M.S.) and PhD in Electrical Engineering or Computer Science  

The Master of Science (M.S.) and Doctor of Philosophy (Ph.D.) programs emphasize research preparation and experience. 

Joint Bachelors/Masters (5th Year M.S.)

This program is available only to Berkeley EECS and CS L&S Undergraduates. It is a five year combined Bachelor/Master's program geared toward outstanding and highly motivated students who desire a program of study that offers greater breadth than is practical in the B.S. or B.A. programs alone.

Master of Arts (M.A.) in Statistics

Professional master's program candidates are engaged in a full-time program for one year (with a possibility of a third semester depending on circumstances). The program is designed to prepare students for careers in industries that require statistical skills.

Ph.D. in Statistics

The Statistics Ph.D. program welcomes students from a broad range of theoretical, applied, and interdisciplinary backgrounds, and provides rigorous preparation for a future career in statistics, probability, or data science. Students in the Ph.D. program take core courses on the theory and application of probability and statistics during their first year.

Designated Emphasis in Computational and Data Science and Engineering

The College of Computing, Data Science, and Society (CDSS) sponsors a Designated Emphasis in Computational and Data Science and Engineering, a program committed to the development of new curricula and expanded programs aimed at the development and use of numerical and computational tools to further research across multiple disciplines.

Discover the Best Data Science Programs in California: Campus and Online Options

Data science has become an essential field in today’s world, driving decision-making and innovation across various industries. California, a global leader in technology and innovation, has emerged as a hub for data science education, attracting students from all over the world. With a plethora of data science programs California offers, specializations, and opportunities, pursuing a data science degree in the Golden State provides a solid foundation for a successful career. Let’s dive into the best data science programs, professional development opportunities, and career prospects in California.

Key Takeaways

Discover the best data science programs in California, offering undergraduate and graduate degrees on-campus or online.

Specialize and concentrate in various aspects to develop skills for a successful career with high job growth rate and competitive salaries.

Take advantage of professional development opportunities such as internships, networking events, mentorship programs, scholarships & financial aid options.

Top Data Science Programs in California

California is home to some of the most prestigious universities offering world-class data science programs. These institutions provide a diverse range of undergraduate, graduate, and online programs, catering to the needs of aspiring data scientists with varied interests and goals. California’s thriving tech scene and numerous data science events further enhance the learning experience, connecting students with industry experts and potential employers.

From the renowned University of California system to private institutions such as Stanford and USC, students have an array of options to choose from. Depending on their career aspirations and preferences, students can focus on specific disciplines within data science, including data management, statistical modeling, and machine learning. We will delve into a detailed examination of top data science programs in California.

Undergraduate Data Science Programs

For students looking to pursue an undergraduate degree in data science, California offers a wide array of programs with diverse specializations. These programs typically require a background in statistics or computer science and cover core data science techniques, such as machine learning and data visualization. Some universities offer specializations in sociological, economic, mathematical, and computational analytics, allowing students to tailor their education to their specific interests.

Introductory ⭐

• Harvard University Data Science: Learn R Basics for Data Science
• Standford University Data Science: Introduction to Machine Learning
• UC Davis Data Science: Learn SQL Basics for Data Science
• IBM Data Science: Professional Certificate in Data Science
• IBM Data Analysis: Professional Certificate in Data Analytics
• Google Data Analysis: Professional Certificate in Data Analytics
• IBM Data Science: Professional Certificate in Python Data Science
• IBM Data Engineering Fundamentals: Python Basics for Data Science

Intermediate ⭐⭐⭐

• Harvard University Learning Python for Data Science: Introduction to Data Science with Python
• Harvard University Computer Science Courses: Using Python for Research
• IBM Python Data Science: Visualizing Data with Python
• DeepLearning.AI Data Science and Machine Learning: Deep Learning Specialization

Advanced ⭐⭐⭐⭐⭐

• UC San Diego Data Science: Python for Data Science
• UC San Diego Data Science: Probability and Statistics in Data Science using Python
• Google Data Analysis: Professional Certificate in Advanced Data Analytics
• MIT Statistics and Data Science: Machine Learning with Python - from Linear Models to Deep Learning
• MIT Statistics and Data Science: MicroMasters® Program in Statistics and Data Science

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Graduates of undergraduate data science programs in California have gone on to work at large technology firms, various levels of government, or continued their education through online data science programs. With a strong foundation in data science, students can embark on rewarding careers in a rapidly growing field.

Graduate Data Science Programs

Graduate data science programs in California, including data science master’s program, provide students with advanced knowledge and skills in the field, preparing them for leadership roles and specialized career paths. Renowned institutions such as Stanford, USC, and UC San Diego offer both on-campus and online graduate programs in data science, covering areas like predictive analytics, machine learning, and applied statistics. Enrolling in a data science university can be a great step towards a successful career in this field.

These programs, often leading to a Master of Science degree, typically take one to two years to complete and require a bachelor’s degree in a relevant field, such as computer science or statistics. Students can expect to learn advanced techniques in data analysis, statistical modeling, and machine learning, equipping them with the expertise needed to excel in data-driven industries.

Online Data Science Programs

For students seeking flexibility and a multidisciplinary approach, online data science programs offered by top California universities, such as UC Berkeley and UCLA, provide an excellent option. These programs offer:

Convenience of online learning

Rigor and quality of traditional on-campus programs

Opportunity to gain valuable skills and knowledge without geographical constraints

Online data science programs typically include live class meetings, document sharing, group activities, and recorded lectures for on-demand access. Students acquire key skills in machine learning to compute solutions and inspect outcomes. They also master the ability to scale up from thousands to billions of data points through data science online courses, becoming an online master in this field.

With a wide range of online data science programs available, students can find the perfect fit for their needs and career goals.

Community College Data Science Programs

Community college data science programs in California offer an affordable and accessible education option for those interested in pursuing a career in data science. Highly regarded community colleges such as Santa Barbara City College, Skyline College, and City College of San Francisco provide data science programs covering essential topics like machine learning, statistics and probability, and data warehousing.

Admission requirements for these programs may include completing prerequisite courses in calculus, linear algebra, and computer science, as well as meeting general education requirements and maintaining a minimum GPA. With community college data science programs, students can gain a solid foundation in the field while keeping their educational expenses in check.

Specializations and Concentrations

Data science is a vast field, and students in California have the opportunity to specialize in various areas such as business analytics, big data analytics, and artificial intelligence. These specializations allow students to focus on specific aspects of data science, honing their skills and expertise to excel in their chosen career paths.

Choosing a specialization enables students to align their education with their interests and professional goals. With a diverse range of specializations and concentrations available in California, data science students can thrive in this ever-evolving field and make a significant impact across various industries.

Business Analytics

Business analytics programs in California focus on using data to drive business decisions and strategies, equipping students with the skills needed to excel in data-driven organizations. These programs cover topics such as:

Predictive analytics

Machine learning

Data analysis

This provides students with a comprehensive understanding of the business world.

Pursuing a specialization in business analytics offers the following benefits:

Hone analytical and decision-making abilities

Acquire practical experience in the field

Find rewarding careers in industries such as finance, healthcare, and technology, where data-driven decision-making is crucial for success.

Big Data Analytics

Big data analytics programs in California teach students:

How to manage and analyze large datasets

Extracting insights and making informed decisions

Emphasize data analysis, data management, and data exploration

Prepare students for careers in industries that rely heavily on data analysis and interpretation.

Specializing in big data analytics equips students with the necessary skills and knowledge to handle large and complex datasets, harnessing data analytics techniques to extract valuable insights. This specialization also provides opportunities to interact with professionals in the data science field, further enhancing students’ learning experience and preparing them for success in their careers.

Artificial Intelligence

Artificial intelligence (AI) programs in California focus on developing intelligent systems and algorithms that can simulate human thought processes and behavior. These programs cover topics such as:

Natural language processing

Data modeling

AI optimization

Algorithm development

These programs allow students to create innovative solutions in various industries.

Specializing in artificial intelligence provides students with expertise in advanced technologies and methodologies that are transforming sectors like healthcare, finance, and transportation. Graduates of these programs can pursue careers in AI research, development, and implementation, making significant contributions to the advancement of this exciting field.

Professional Development Opportunities

In addition to choosing the right data science program and specialization, students in California can further enhance their learning experience and career prospects through professional development opportunities. Networking events, mentorship programs, and internships provide valuable avenues for students to gain real-world experience, connect with industry experts, and develop their skills in the field of data science.

These opportunities not only help students build a strong professional network but also allow them to learn from experienced data scientists and gain insights into the latest trends and innovations in the industry. Leveraging these opportunities will set a solid foundation for success in the future careers of data science students in California.

Internships

Internships are an excellent way for data science students to gain hands-on experience and apply their skills to real-world projects. California is home to numerous tech companies, research institutions, and startups that offer internships in data science, providing students with ample opportunities to develop their skills and build their portfolios.

Some popular data science internships in California can be found at companies such as Adobe, Snowflake, and on platforms like Indeed, LinkedIn, and Chegg Internships. Participating in internships provides students with the opportunity to work on a variety of projects involving data cleaning, analysis, visualization, and machine learning. This not only enhances their practical experience but also allows them to showcase their skills in the field.

Networking Events

Networking events offer data science students in California the chance to connect with fellow students, industry professionals, and potential employers. These events provide opportunities for learning, collaboration, and sharing ideas, fostering a sense of community among data science enthusiasts in the state.

Some notable networking events for data science students in California include the Open Data Science Conference (ODSC), the Data Science Salon, and the Data Science Innovation Summit. These events typically feature workshops, panel discussions, and networking opportunities, allowing students to expand their knowledge, share ideas, and build connections within the data science community.

Mentorship Programs

Mentorship programs connect data science students with experienced professionals who can offer guidance, support, and insights into the data science field. Participating in a mentorship program can provide students with valuable advice, networking opportunities, and industry insights, helping them navigate their careers and develop their skills.

Some notable mentorship programs for data science students in California include:

The Data Science Mentorship Bootcamp by Magnimind Academy

The Data Science Social Good Summer Program at Stanford University

The Research Mentorship Program at UC Santa Barbara

The Insight Data Science Fellowship

These programs facilitate collaboration, learning, and professional growth, setting students up for success in the data science field.

Career Prospects for Data Scientists in California

The career prospects for data scientists in California are promising, thanks to the growing demand for data-driven decision-making, technological advancements, and the presence of data science programs in the state. With a projected job growth rate of 36% by 2031 and an estimated 13,500 new job openings per year, data scientists in California can expect a bright future in the field.

The average salary for data scientists in California is $133,110 per year, with high-demand industries such as finance, healthcare, and technology offering competitive salaries and diverse career opportunities. As the demand for data scientists continues to grow, professionals in the field can look forward to a thriving job market with ample opportunities for growth and success.

Job Growth Rate

The job growth rate for data scientists in California is projected to be 36% from 2021 to 2031, which is greater than the national average. This growth can be attributed to the increasing demand for data-driven decision-making, technological developments, and the expansion of industries that rely on data analysis.

This positive job outlook assures data science students in California of the high demand for their skills and expertise. Pursuing a data science degree in California, coupled with leveraging the multitude of professional development opportunities, paves the way for students to have a successful and rewarding career in this rapidly growing field.

Average Salary

Data scientists in California enjoy a competitive average salary of $133,110 per year. This salary can vary depending on factors such as experience level, industry, and location. For instance, data scientists working in the San Francisco metropolitan area can expect higher salaries compared to other regions in the state.

The attractive salary prospects for data scientists in California reflect the value that organizations place on their expertise and skills. Pursuing a data science degree along with a specific area of interest specialization can boost students’ earning potential and promise long-term career success in this burgeoning field.

High-Demand Industries

The high-demand industries for data scientists in California include technology, healthcare, and financial services. In these industries, a data scientist plays a crucial role in analyzing, managing, and exploring data, using data analytics techniques to extract insights and make informed decisions.

Focusing their education and professional development on these high-demand industries enhances the likelihood of data science students in California securing rewarding and fulfilling job opportunities in data science careers. As the demand for data scientists and data science professionals continues to grow in these industries, professionals with the right skills and expertise will be well-positioned to excel in their careers.

Scholarships and Financial Aid

Pursuing a data science degree in California can be a significant investment, but there are numerous scholarships and financial aid opportunities available to help students offset the costs. University-based scholarships and external scholarships are available for data science students in California, providing financial support to those in need and recognizing academic achievements.

Leveraging these scholarships and financial aid opportunities enables data science students in California to concentrate on their studies and professional development without the distraction of financial concerns. With the right support, students can pursue their passion for data science and achieve success in their chosen career path.

University-Based Scholarships

University-based scholarships for data science students in California are available at institutions such as the University of San Francisco, UC Berkeley, and Stanford University. These scholarships typically recognize academic achievements and may be awarded based on factors such as merit, financial need, or other criteria.

To apply for university-based scholarships, students should research the available opportunities at their chosen institutions, paying close attention to the application deadlines and requirements. Securing a scholarship alleviates the financial burden of education, allowing students to concentrate on honing their skills and expertise in the data science field.

External Scholarships

External scholarships for data science students in California can be found on websites such as mastersindatascience.org and knowledgehut.com. These scholarships are offered by various organizations and may be awarded based on merit, financial need, or other criteria. Some scholarships may also be specifically designed for minority students or those pursuing particular specializations within data science.

In order to apply for external scholarships, students need to investigate the available opportunities while being mindful of the application deadlines and requirements. By securing an external scholarship, students can receive additional financial support to help cover the costs of their data science education and focus on their professional development.

California offers a wide range of opportunities for students pursuing a data science degree. With numerous top-ranked universities, diverse programs and specializations, and ample professional development opportunities, the Golden State is an ideal destination for aspiring data scientists. As the demand for data-driven decision-making continues to grow, students in California can look forward to a thriving job market and rewarding career prospects. By taking advantage of the many resources available, students can set themselves up for success and make a significant impact in the world of data science.

Frequently Asked Questions

Which is best program for data science.

TensorFlow is the most popular open-source data science tool, providing ML and DL libraries to build data analysis and ML algorithms. It also offers great visualization features, making it the best program for data science.

Is data science major worth it?

A data science degree can help you land a lucrative job, so it is well worth the time and money for many. However, there are more affordable options available too.

Is data science a 4 year degree?

Data science can be pursued through a four-year bachelor’s degree or a shorter boot camp. Alternatively, you can obtain a master’s degree in data science which generally requires less than one year of study.

Which Cal states offer data science?

California State Universities offering Data Science programs include San Diego State University, California Polytechnic State University, San Jose State University, and the University of California, Berkeley. These institutions provide excellent academic standards for students to pursue their studies in data science.

What types of data science programs are available at universities in California?

Various data science programs are available at universities in California, including undergraduate, graduate, masters, and PhD programs.

43 Best colleges for Data Science in California, US

Updated: February 29, 2024

• Art & Design
• Computer Science
• Engineering
• Environmental Science
• Liberal Arts & Social Sciences
• Mathematics

Below is a list of best universities in California ranked based on their research performance in Data Science. A graph of 1.69M citations received by 32.4K academic papers made by 43 universities in California was used to calculate publications' ratings, which then were adjusted for release dates and added to final scores.

We don't distinguish between undergraduate and graduate programs nor do we adjust for current majors offered. You can find information about granted degrees on a university page but always double-check with the university website.

1. Stanford University

For Data Science

2. University of California - Berkeley

3. University of California-San Diego

4. University of California - Los Angeles

5. University of Southern California

6. University of California - San Francisco

7. University of California - Santa Barbara

8. University of California - Irvine

9. University of California - Davis

10. California Institute of Technology

11. University of California - Riverside

12. University of California - Santa Cruz

13. San Jose State University

14. San Diego State University

15. Naval Postgraduate School

16. University of California - Merced

17. Claremont Graduate University

18. Palo Alto University

19. Santa Clara University

20. California Polytechnic State University - San Luis Obispo

21. University of San Francisco

22. California State University - Fullerton

23. San Francisco State University

24. Humboldt State University

25. California State University - Sacramento

26. Sanford Burnham Prebys Medical Discovery Institute

27. california state polytechnic university - pomona.

28. California State University - Fresno

29. Chapman University

30. California State University - Long Beach

31. Loma Linda University

32. California State University - Northridge

33. California State University - Los Angeles

34. Pomona College

35. Loyola Marymount University

36. California State University - East Bay

37. California State University - San Bernardino

38. University of San Diego

39. California State University - Bakersfield

40. California State University - Chico

41. University of the Pacific

42. Harvey Mudd College

43. California State University - Monterey Bay

Closest to California states to learn Data Science

Computer science subfields in california.

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Data Science and Analytics Programs in California

California is home to some of the best data science and analytics programs in the nation. The Golden State has a thriving tech culture, rife with opportunities for students at every level. The latest Bureau of Labor Statistics data shows that 18.47 percent of all US data scientists work in California.

And with an average pay of $103,500 for most data science jobs, the demand for data science courses in California shouldn’t be surprising. With hundreds of certifications, boot camps, on-campus and off-campus master’s degrees, and PhD programs, data science offers students a unique way to combine their software, statistics, and math interests to create innovative solutions. 

If you plan to get into data science or analytics in California, you’ll need to know what courses will help you get there.

Read on about California’s top data science and analytics programs.

Data Master’s Programs in California

California offers online and on-campus master’s degree programs in business analytics, data analytics, and data science. If you are looking to change career paths or want to advance your undergraduate degree, consider enrolling in one of the following master’s degree programs offered by universities and colleges in California: 

Masters of Business Analytics

Master of Business Analytics focuses on applying modern data science, machine learning, and optimization to solve real-world business problems. 

Graduates often find well-paying jobs solving business challenges in technology companies and startups in California, where analytics plays a huge role in business success.

Some of the master of business analytics programs available in California include:

Online Master of Science in Business Analytics- Touro University

• Class type: 100 percent online
• Course duration: one year
• You can earn the degree in 12 months by taking two courses per term for six consecutive terms.

Master’s in Business Analytics – Hult International Business School 

• Class type: Campus
• Course duration: 11 months

Master of Science in Business Analytics – UC Irvine – Merage School of Business

• Class Type: On-campus
• Course duration: 11-13 months

Master of Science in Business Analytics (MSBA) – Golden Gate University

• Course type: Online and on-campus 
• Course duration: 4 – 5 semesters 

Master’s of Data Analytics 

Master of data analytics empowers graduates with the skills of using big data for business decision-making and planning. This course builds students’ proficiency in data mining tools and data analysis methodologies.

Graduates can take roles such as big data architect, computer and information system manager, and logistician.

Some of the masters of data analytics programs available in California include:

Master of Analytics – University of California, Berkeley

• Course type: In-person 
• Course duration: three semesters 
• This course also includes a 10-week internship 

MS in Data Analytics – Alliant International University

• Course type: Campus-based program
• Course duration: 14 months 

MS in Healthcare Analytics – Alliant International University

• Course type: Full-time campus-based
• Course duration: one year 

Master of Science in Big Data Analytics – San Diego State University

• Course type: Full-time on-campus
• Course duration: two years

Master’s of Data Science 

Masters in data science earns you a broad skill set that you can apply to a vast array of tech-related careers such as computer programming, data architecture, and data engineering. 

You learn essential concepts such as applied statistics, database systems and preparations, and practical machine learning. You also learn programming languages such as R, Python, and SQL.

Some of the masters in data science programs available in California include:

MS in Data Science -San Francisco University

Master of Science in Engineering in Data Science – University of California, Riverside

• Course type: Online course 
• Course duration: one year, one month. 

Applied Data Science – University of Southern California

• Course type: On-campus and online

Data Science Master – the University of California, Irvine (UCI)

• Course type: On-campus
• Course duration: 15 months

Online Data Science Programs in California

If you wanted to study at a university just a few years ago, you could only do so by attending physical classes. Evening classes were the only way that professionals could juggle work and study. But not anymore. 

Today, if you want to get a master’s degree in data science, you can do so online. 

Like on-campus programs, online data science programs prepare students for work as data analysts and data scientists. Students will learn to use programming, statistics, modeling, and machine learning to solve real-world problems.

If you are ready to learn data science from the comfort of your computer at home, below are online masters of data science programs to consider: 

Master of Data Science, UC San Diego

• Course level: Beginner
• Course duration: 2 years
• Price: Approx. $15,820/year

The MDS program at UC San Diego is a joint degree between the School of Engineering and Computer Science and the Halıcıoğlu Data Science Institute (HDSI). The program draws from the expertise of these two departments to equip students with data-handling and analysis skills through a rich course curriculum that includes: 

• Three foundation courses: Python, probability and statistics, and machine learning 
• Three core courses: Data management, big data analytics with Spark, and data mining 
• Capstone project

Students can also choose between courses such as natural language processing (NLP), and unsupervised learning, among others. 

The program culminates in a research project during the third year, giving students experience in data science research. This program is highly ranked and has many employees from large companies as alumni. 

The coursework is rigorous, but the program is designed to be flexible so that students can fit their schedules around work and other responsibilities. 

Master of Science in Data Science, National University

• Price: $17,238

This program is designed for adult learners and covers 14 months. However, the National University offers a flexible timeline, spread over 4-week courses. You can thus start sooner or finish faster or have the flexibility to juggle between family, work, and studies.

This program offers career-focused specializations in the following fields:

• Artificial intelligence and optimization
• Business analytics
• Database analytics
• Health analytics

The prerequisite to enrolling in NU’s master of science in data science program is previous industry or study experience in statistics, math, engineering, computer programming, or science. You also need a minimum GPA of 2.50.

Master of Science in Data Science, Northcentral University

• Course duration: 30 credit hours | 23 months normal duration
• Price: $30,420

The Master of Science in Data Science at Northcentral University is a very flexible online program covering a comprehensive curriculum. It supports adult and non-traditional learners, with accessibility and educational flexibility being the private university’s biggest aims.

To enroll in the MS in Data Science program, you must hold an undergraduate degree. However, no test scores, prerequisite courses, or minimum GPA are required.

Students can start the program every week on Monday. The required courses to complete the program include:

• Principles of data science
• Quantitative research design
• Databases and business intelligence
• Big data integration
• Data mining
• Quantitative methods for data analytics and business intelligence
• Inferential statistics and predictive analysis
• Critical analysis, interpreting, and reporting data
• Data visualization
• Strategic management of data, information, and knowledge for data science

The admissions into this program are very flexible, and the course favors students with less academic preparation.

Online Master’s in Data Science, UC Berkeley

• Price: Approx. $2,712 per unit (fee is not inclusive of campus fees)

The Master of Data Science (MDS) at the University of California, San Diego is a top-ranked online master’s degree program in data science. With an emphasis on hands-on training, students learn to apply best practices and techniques from data science in real-world settings. 

Students can expect to learn how to set up data pipelines, work with big data, and think like data scientists. The curriculum also includes courses in statistics and probability theory. 

There are two tracks within the MDS: 

• Machine learning 
• Data mining/Business intelligence 

The courses within these tracks vary widely. For example, ML tracks include Bayesian models, machine learning algorithms, and statistical modeling courses. On the other hand, BI tracks focus on data mining tools such as R and SQL. 

Some electives allow students to choose topics such as Python for data science, designing data scraping pipelines with Scrapy, and visualizing data with D3.

This course equips students in the following areas: 

• Data cleansing
• Research design
• Data engineering
• Data mining and exploring
• Machine learning
• Information ethics and privacy
• Statistical analysis

Master of Science in Applied Data Science, University of Southern California  

Students with bachelor’s degrees in computer science, engineering, social science, and other scientific disciplines can get the training to pursue a data science career via this program.

Upon course completion, students will have learned: 

• Data handling techniques
• Data science programming with Python 
• Data mining 
• Working with big data 
• How to handle data within databases 

The program offers a completely immersive experience in data science and prepares students to embrace their future roles as data scientists or analysts. 

Example Data Science Courses in California

Data science and analytics bootcamps in california.

Are you interested in learning about data science but don’t have the time or budget for an advanced degree? A bootcamp will provide the technical training you need to land your first data science job.

Tech bootcamps are short-term courses designed to teach technical skills and knowledge in a specific domain. Data science boot camps offer career training and can help you get a job as a data scientist or data engineer after graduation. Bootcamps are typically three months long, shorter than most other programs.

While boot camps are not for everyone, they can be a good fit for some people. If you’re looking for hands-on experience and some programming experience, a boot camp might be right for you.

We have compiled a list of popular data science boot camps below:

Data Science PhD Programs in California

Many people understand what data science is, but they aren’t always sure where or how it’s used. 

To better understand the field, you should look at where data PhDs work and what research they conduct. Data science PhDs are researchers who use data to address real-world problems.

There are two main reasons why data PhDs are essential: 

• The amount of data being generated is increasing dramatically. Hence there is a growing demand for skilled data scientists to help analyze and make sense of the data. 
• Data is becoming increasingly important in all research fields, including health care, business, social sciences, and law enforcement. 

That said, there are many different types of PhDs in data science: 

• Some focus on specific areas such as machine learning and deep learning. 
• Others are focused on more general topics like data mining or data visualization. 
• There are also interdisciplinary areas where PhDs cut across fields like engineering, mathematics, and statistics.

Most PhDs work in academia, government research facilities, or industry. Data PhDs tend to be found in disciplines that use data, such as science and engineering. Other PhDs work full-time or part-time with other researchers or by themselves, or as consultants.

Regardless of their position, they will likely spend most of their time working with computers and software. Some also conduct field research as part of their work duties. The pace of their work usually depends on the task at hand and how quickly they need results.

Examples of data science Ph.D. programs in California include USC Data Science and Operations and PhD in Computational and Data Sciences from Chapman University .

Five In-Demand Analytics Jobs in California

Suppose you have a solid quantitative background and a passion for data. In that case, you have the potential to be an analytics expert at a startup, medium-sized business, or even a large corporation.

Currently, there are many available positions for analytics professionals in California. This could be the right place to look for a challenging and rewarding career. Here are some of the most in-demand jobs in California:

1.       Data Analyst

• Education level: Bachelor’s degree or master’s. 
• Average salary/year: $90,307 (about 5 percent above national average)
• Work environment: From freelance, remote to full-time in the office
• Data analysts are responsible for analyzing data to produce actionable insights that help businesses make informed decisions about their operations. They perform complex mathematical and statistical calculations to extract meaning from large numerical data sets. They also develop models to predict future outcomes based on previous events and trends.

2.       Analytics Consultant

Education level: Bachelor’s degree or master’s in a related field. 

• Average salary/ year: $107,892
• Work environment: remote or part-time/full-time in the office
• An analytics consultant plays a vital role in helping businesses understand their customers’ needs, analyze their data, and use it to improve their products and services. They work with clients to design custom solutions to solve individual problems or optimize existing ones. They also advise organizations on building better customer relationships through data collection, analysis, and information sharing.

3.       Data Visualization Expert 

• Education level: Bachelor’s degree or master’s in data science, statistics, or related field
• Average salary/ year: $111,345
• Becoming a data visualization expert will require artistic talent and a solid understanding of data analysis. The goal is to create graphics and charts to help your employer make better decisions. This could be anything from infographics used on your company website or presentations for investors or clients.
• The best way to become a data visualization expert is by taking classes at your local college or university. The University of California – Berkeley (UCB) offers courses for free online that teach you how to use various data visualization tools like Tableau.

4.       Data Visualization Assistant:

• Education level: Bachelor’s degree. Masters preferred
• Average salary/ year: Hourly pay ($25.96to $77.64)
• If you don’t have prior work experience, you should consider becoming a data visualization assistant. This position requires little experience, but it does require strong analytical skills and an eye for design. 
• As a data visualization assistant, your primary responsibilities will involve creating high-quality visualizations using software such as Excel or Photoshop. If you can do this well, you might get promoted to a full-time data analyst position at the same company.

5.       Data Visualization Designer:

• Average salary/ year: $87,000
• Work environment: Freelance, remote, or in-office
• If you already have experience creating visualizations or a degree in computer science, you might consider becoming a designer. This position requires strong analytical skills and strong communication skills, especially when presenting your findings to clients or investors. As a data visualization designer, your primary responsibilities will involve creating high-quality visualizations using various software such as Tableau. You should also communicate well with other team members about what kind of data needs to be collected and analyzed so that the company can make the best decisions possible.

Frequently Asked Questions

California is renowned for its thriving tech culture and hosts some of the top data science and analytics programs in the U.S. This makes it an ideal place for students interested in these fields.

California offers a range of programs including online and on-campus master’s degrees, PhD programs, and bootcamps in business analytics, data analytics, and data science.

Data science bootcamps in California are short-term, intensive courses designed to provide technical training for those looking to enter the data science field quickly. They are ideal for individuals without the time or resources for an advanced degree​

Data science PhD graduates often engage in research to solve real-world problems and find opportunities in various sectors where data analysis is crucial.

There are many available positions for analytics professionals in California, spanning startups, medium-sized businesses, and large corporations.

Related Resources

• What is Data Analytics?
• Data Science Certification
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What we offer related to Data Science!

CSUEB Statistics students face lower competition for course availability.

We offer courses directly related to Data Science at the undergraduate and graduate levels. Topics include:   R   for Data Science, Data Visualization, Statistical Learning, Predictive Modeling, Training and Test Data, Statistical Natural Language Processing, Applied Deep Leaning, Time Series, Bayesian Statistics

Most important requirement for the   BS Statistics Concentration in Data Science or Minor in Data Science   is   interest   – the program is applied and hands on.  Study Data Science in the CSU East Bay College of Science.  Smaller undergraduate classes ~35 students per class.  We describe our major as: “Touch data” “Compute-more” “Calcu-less”

Most important application requirement for the   MS Statistics Option in Data Science   is   interest   – please apply for Fall Semester, but if you miss the deadline you can start Fall through OpenU and apply for Spring Semester.  Study Data Science in the CSU East Bay College of Science.  Our MS program is designed for continuing students who have completed any undergraduate degree and some prerequisite courses and for working adults.  Complete the degree in two years, 2 afternoons or 2 evenings per week.  Reasonable   price   – no $80,000 price tag, no CSU Business College $270 per UNIT fee, save approximately $8,640.  Program can be completed in 3 semesters by taking class four days a week, see the Graduate Advisor for details upon admission.  Afternoon and Evening classes.  Smaller graduate classes ~25 students per class.  We describe our program as:  “Touch data” "Work with small data to medium data to big data"  "100s of rows to 10's of millions to a billion+ rows of data"

Diversity of technical background valued, you can start from scratch or have a PhD or MD, retired professionals welcome!

DATA SCIENCE WORKGROUP F2

On Friday's at 2pm the Data Science Workgroup meets. In the Fall Semester the STAT 694 can be taken for credit. Each semester students work on a research project applying Data Science Methods to data of interest.

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Berkeley Berkeley Academic Guide: Academic Guide 2023-24

Applied data science.

About the Program

The Graduate Certificate in Applied Data Science, offered by the UC Berkeley School of Information, introduces the tools, methods, and conceptual approaches used to support modern data analysis and decision-making in professional and applied research settings. It exposes students to the challenges of working with data (e.g., asking a good question, inference and causality, decision-making) as well as to the new tools and techniques for data analytics (machine learning, data mining, and more).

The certificate is particularly designed to meet the needs of the graduate students in Berkeley’s professional schools — both professional master’s students and doctoral students — as well as graduate students in the social sciences and the arts & humanities.

The need for expertise in data analytics continues to grow in all organizations and disciplines. Graduate students in every field are now working with data from new sources: websites, electronic medical records, transaction records, sensor networks, smart phones, and digitized records and documents. The analytical tools and methods traditionally used to derive insights from structured and well-curated data sets (census, surveys, and administrative data) are not sufficient for this new, unstructured and often user-generated data.

The Graduate Certificate in Applied Data Science provides hands-on practice working with unstructured and user-generated data to identify new ways to inform decision-making. The curriculum educates professionals and scholars to be intelligent consumers of data science techniques in a variety of domains, with a foundation of skills for applying these techniques in their own domains.

Visit Program Website

Any UC Berkeley graduate student in good standing may apply. To apply, students should submit the following materials on the School of Information website :

• a letter of intent,
• a proposed study plan,
• a description of their Python programming and statistics competencies,
• their curriculum vitae or resume,
• their Berkeley course transcript.

Applications are accepted twice a year, in the middle of the fall and spring semesters.

Students may apply at any time during their UC Berkeley graduate career, either before or after taking courses that would count toward the certificate.

Certificate Requirements

Prerequisites.

Applicants must:

• Be registered and enrolled in a graduate degree program at UC Berkeley
• Be in good academic standing
• Meet course and subject matter prerequisites for courses taken in the certificate program, typically including Python programming and basic statistics knowledge.

The certificate requires three 3-unit courses, taken from the following approved lists:

An introductory data science class

A course in analytical methods and techniques of data science

An additional elective: either a domain-specific data science course or a second methods course.

Courses should be taken for a letter grade and must be completed with a grade of B or higher.  At least one of these courses must be an INFO course offered by the School of Information.

1. INtroductory data science course

 2. analytical methods and techniques of data science.

Students must take at least one course from this list:

3. Electives

Students must take one domain-specific data science course from the following list or a second methods course from the list in Section 2 above:

Contact Information

School of information, applied data science certificate.

[email protected]

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Post Graduate Program in Data Science

Empower your future: data science training.

Learn data science and generative AI skills with this data science course. Indulge in a high-engagement learning experience that leverages Caltech’s academic excellence and IBM’s industry prowess in data science.

Learn data science and generative AI skills with this data science course. Indulge in a high-engagement learning experience that leverages Caltech’s a... Read more

• Program Duration 11 months
• Learning Format Online Bootcamp
• Admission closes on 17 Apr, 2024

Data Science Course Highlights

Embark on your tech journey with Caltech’s PG in Data Science. Master the art of data analysis and predictive modeling and earn a prestigious certificate.

Caltech CTME

Program certificate and up to 14 CEU credits from Caltech CTME

Masterclasses delivered by distinguished Caltech CTME instructors

Gain Generative AI Mastery

Dedicated course on Generative AI, Prompt Engineering, ChatGPT and much more

Gain exposure to ChatGPT, DALL-E, Midjourney and other prominent tools

Experiential Learning in a Cohort-based Program

Application-based practical training from leading industry experts

6 months of applied learning: 25+ hands-on projects with seamless access to labs

GET PROGRAM DETAILS

Our alumni work at.

FOR ENTERPRISE

Program outcomes.

• Program completion certificate from Caltech CTME
• Learn about Generative AI and stay ahead of the curve
• Exposure to prominent tools such as ChatGPT, Google Bard, Midjourney
• Earn up to 14 CEUs and Circle Membership from Caltech CTME

Data Science Course Curriculum

Welcome to this PG in Data Science, developed and presented with Caltech CTME and IBM, which will help you become an expert in the data science domain.

In this course, you will develop essential Python skills that serve as a crucial foundation for your progress throughout the program.

Enroll in this course to acquire essential knowledge for effectively working with SQL databases and leveraging them in your applications. Throughout the course, you will gain a solid understanding of SQL statements, conditional statements, commands, joins, subqueries, and various functions, empowering you to manage your SQL database for scalable growth proficiently.

Kickstart your learning by getting an understanding of the Python language and its libraries, and writing scripts using the Jupyter-based lab environment with this Python for Data Science course.

This course comprehensively explores data science essentials, covering data preparation, model building, and evaluation. Participants will delve into fundamental Python concepts, including strings, Lambda functions, and lists. Additionally, they will gain proficiency in essential topics such as NumPy, linear algebra, and statistical concepts, which include measures of central tendency and dispersion, skewness, covariance, and correlation.

This course comprehensively explores diverse machine learning types and their practical applications. Participants will gain insights into the machine learning pipeline, delving into supervised learning, regression models, and classification algorithms. Additionally, the course covers unsupervised learning, clustering techniques, and ensemble modeling. Participants will also evaluate well-known machine learning frameworks like TensorFlow and Keras.

This Tableau course unlocks a comprehensive understanding of creating captivating visualizations, optimizing data organization, and designing informative charts and dashboards to facilitate astute business decisions. Throughout the program, you'll delve into data visualization concepts, gain proficiency in crafting diverse combo charts and stories, and learn to work adeptly with filters, parameters, and sets. Additionally, you'll master the art of constructing interactive dashboards.

The Data Science Capstone project provides a valuable opportunity to apply the skills you have acquired during this program. With the guidance of dedicated mentors, you will address a real-world data science problem aligned with industry standards. This comprehensive project covers data processing, model building, and reporting business results and insights. It is the final step in your learning journey and enables you to demonstrate your data science expertise to potential employers.

Skills Covered

• Conversational AI
• Data Visualization
• Descriptive Statistics
• Ensemble Learning
• Explainable AI
• Exploratory Data Analysis
• Generative AI
• Inferential Statistics
• Large Language Models
• Model Building and Fine Tuning
• Prompt Engineering

Tools Covered

Industry Projects

Data science course program advisor, data science course fee.

Pay in Installments

You can pay monthly installments for Post Graduate Programs using ClimbCredit payment option with low APR and no hidden fees. .

Eligibility Criteria

• A bachelor's degree with an average of 50% or higher marks
• Basic understanding of programming concepts and mathematics
• 2+ years of work experience preferred

Best Suited For

• Software Engineers
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• Aspiring Data Science Professionals
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• Product Managers

How to Apply for Data Science Course

Tell us a bit about yourself and why you want to do this program

An admission panel will shortlist candidates based on their application

Selected candidates can begin the program within 1-2 weeks

Demand for Data Science Course in 2024

Data Science has experienced a significant surge in recent years, primarily driven by an exponential increase in data generation and the need for businesses to leverage this data effectively. This Post Graduate Program in Data Science equips you with cutting-edge skills to manage, analyze and interpret complex data. It makes you invaluable to employers and areas around it. According to the Bureau of Labor Statistics, the demand for data science professionals is projected to grow 15% by 2029, much faster than the average for all occupations.

Data science professionals are instrumental in helping organizations make strategic decisions in a world that's becoming increasingly interconnected. Caltech’s comprehensive Data Science Post Graduate Program provides a robust foundation in machine learning, data visualization, and predictive analytics, enhancing your ability to generate actionable insights from data.

Data Science Course FAQs

What is a pgp data science certification.

A PGP in data science certification is an intensive training program designed to teach participants the skills needed to become a data scientist. The program curriculum covers essential topics such as statistics, programming, visualization, data science and machine learning. They often involve hands-on projects and real-world applications to provide participants with practical experience. Upon completion, participants receive a PG certification that validates their skills and knowledge in the field.

Other Programs you may be interested in

Caltech and simplilearn collaboration.

Founded in 1891, Caltech is a world-renowned science and engineering institute that marshals some of the world’s brightest minds and most innovative tools. The contributions of Caltech’s faculty and alumni have earned national and international recognition, including 45 Nobel Prizes and 71 National Medals of Science. Caltech CTME has chosen to team with Simplilearn to co-deliver these online professional programs. Simplilearn's award-winning immersive learning model delivered via live virtual classes focuses on applied learning to create immediate career impact. 

Other Programs

• Post Graduate Program in DevOps
• Post Graduate Cloud Computing Program
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The online Master of Data Science from University of California San Diego

Want to learn more, get important information, dates, and updates.

in Public Colleges ranked by Forbes 2022

In data analytics/science ranked by us news, accelerate your career, without putting it on hold.

UC San Diego’s 100% online Master of Data Science program is designed for working professionals seeking a competitive edge in the rapidly expanding data science industry.

Fall 2024 Start Application Deadlines

Nov. 15, 2023.

Applications Open

Mar. 15, 2024

Priority Deadline

Jun. 5, 2024

Final Deadline

UC San Diego online Master of Data Science (MDS) | Overview

Online learning without compromise.

Courses are developed by world-renowned UCSD faculty in collaboration with online learning experts to ensure the best possible experience. Connect with instructors via email, discussion boards, video conferencing, and more.

You’re connected to your instructors, UCSD’s exceptional network of career and professional development resources, personalized librarians, and your cohort - no matter where you are.

More Information

Earn your degree in as little as two years, 3 foundations.

Learn essential concepts and build necessary skills

Explore central topics of data science

3 Electives

Explore your unique data science interests

10-week, real-world research project

Preparing the next Generation of Data Scientists

Since 2018, UC San Diego’s Halıcıoğlu Data Science Institute (HDSI) has emphasized an interdisciplinary approach to investigating the world’s data. HDSI in collaboration with the Department of Computer Science and Engineering (CSE) has designed a program that will help students gain a deep understanding of data and the technical skills required to collect, analyze, and present their findings. They will also understand the ethical implications of their work as we continue to generate more data than ever before.

Join a Powerful, Global Network

UCSD alumni are some of the most exceptional in the world. With a vast network of connections, they are able to offer unique insights and perspectives on a variety of topics. UCSD alumni are also highly sought-after by employers, making them an invaluable asset to the university. The UCSD alumni network is truly one of a kind, and its members are poised to make a significant impact on the world. UCSD is fortunate to have such an outstanding group of alumni, and the university is proud to be associated with them.

MASTER OF DATA SCIENCE

Empowering innovation.

Data science has emerged as a crucial force in the technological revolution, bridging the gap between a data-poor past and a future of intelligent systems. 

The Master of Data Science (MDS) program is designed to cultivate expertise in contemporary data science methodologies. By integrating the foundational principles of Statistics and Computer Science, our program equips and empowers students with the necessary skills to thrive in the age of artificial intelligence disruption. 

Candidates may select from our full-time (15-month) or part-time (24-month) pathway, both instructed by esteemed faculty members and researchers possessing extensive experience in data science. The curriculum emphasizes hands-on training in applied probability, mathematical statistics, statistical modeling, computing, machine learning, data management, visualization, and artificial intelligence.

STEM Designated

Eligible for 36 Months of Optional Practical Training

Best Master's in Data Science

Ranked by FORTUNE

85% Placement Rate

ICS Professional Master’s programs boast 85% placement rate within 3 Months of Graduation

The UCI MDS program distinguishes itself with a robust foundation in data science, incorporating a balanced curriculum that accentuates both computer science and statistics. Furthermore, our program encompasses two capstone project courses, providing students with invaluable experience in addressing real-world challenges through data science techniques.

As intelligent systems consume vast amounts of data, data science will be instrumental to the innovation of powerful and versatile AI systems. Graduates of the program will be equipped to adapt to the advancements of an AI-driven future.

We are taking the helm of generating a robust Data Science program to innovate and be leaders in the industry. Our balanced approach makes us a unique catalyst where students can learn and make an impact on society. Bin Nan, Chancellor's Professor and Faculty Director Master of Data Science Department of Statistics

The Donald Bren School of ICS Ecosystem

The Donald Bren School of Information and Computer Sciences at UC Irvine, is one of the leading computing schools in the nation and is strategically centered in the nucleus of Southern California’s TechCoast, which encompasses over 40% of Orange County’s high-tech and biomedical enterprises and one-third of Fortune 500 company offices.

By capitalizing on our internationally renowned faculty and the vigorous industry clusters in life sciences, information technology, aerospace, advanced manufacturing, and digital arts and media, the Master of Data Science program is meticulously crafted to stimulate innovation and propel the data science discipline forward.

Discover Academic and Research Opportunities

Reinforce local businesses and industries, access to resources and capital, nurture a culture of innovation, enhance your network and professional development.

Embark on your degree in a dynamic destination city that provides the resources, capital, and innovative culture requisite for elevating your academic and professional trajectory in data science.

The Master of Data Science program provides flexible learning paths, with both full-time and part-time options, tailored to meet your unique academic and professional demands. Regardless of the pathway chosen, all students enjoy equal access to our rich, comprehensive curriculum and the collective wisdom of our distinguished faculty.

To attain the coveted Master of Data Science (MDS) degree, students are required to successfully navigate through an academic journey comprising 52 units. This includes ten core courses, which form the backbone of data science principles; three elective courses, offering an opportunity to delve into areas of personal interest within the field; and finally, a capstone project that allows students to apply their knowledge to real-world problems, synthesizing and showcasing their learning.

Upon the culmination of this rigorous yet rewarding program, graduates will emerge equipped with a robust blend of technical expertise and professional acumen. This unique combination primes you for a successful career trajectory, enabling you to seamlessly transition into the dynamic world of data science and make your mark.

Take the Next Steps

Learn more about the journey ahead.

Data science seems like the Swiss Army knife of majors in its applicability across fields—I cannot think of an industry that doesn’t make use of data in some way, Adelynn Paik, MDS Student '22

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California Data Science Degree Programs

Consider a sponsored online program currently accepting applicants.

Click to see more featured 100% online data science programs currently accepting applicants for 2024.

With over 70 different data science programs in California, there are quite a few options to choose from. There are also a handful of online data science programs in California that also have campus locations within the state.

All degrees are a Master in Data Science degree , aside from a Graduate Certificate in Data Science offered by Stanford University.

The University of California at Berkeley's Master of Information and Data Science program (a sponsored program, sometimes goes by the acronym MIDS) is a growing degree offering from a top-tier university, offering the degree part-time, full-time, and in an accelerated format for those that qualify.

Click for more online data science programs that are taking applications.

Are there online data science programs in California?

Yes . Here is the list of some of the best online data science degree programs in California that we have found so far.

Full List of the Best California Data Science Degrees

Here is the list of some of the best data science programs online and at campuses in California..

Notice a missing or inaccurate program? Our data is hand-collected and edited. If you notice a missing data science program, please email schools at datascienceprograms.org to enter a program to be reviewed or to adjust a current listing.

In-depth review of a few online Data Science programs in California, Updated for 2024

University of california-berkeley: mids degree.

Completing the program can take between 12 to 32 months depending on the speed chosen. The curriculum is 27 units with core classes focusing on data engineering , data visualization, research design, statistical analysis, and more. Featured courses for the MIDS degree include Applied Machine Learning, Natural Language Processing with Deep Learning, and the legal and ethical issues around data science. There is a capstone project at the end that completes the program.

What courses would look like

Weekly live class meetings will have 18 students at maximum and various features will be available, such as document sharing and group activities. Students have the option to choose a PC or mobile platform for their classes and all lectures will be recorded for on-demand access. There is a need for a week-long residency at the UC Berkeley campus to meet with faculty and other students, as well as meeting with professionals in the data science field.

<Click for admissions information on the Online Master of Information and Data Science program at University of California Berkeley.

Click for more information on the Online Master of Information and Data Science program at University of California Berkeley, which is taking applications for 2024.

National University: MS in Data Science

The San Diego-based college provides a Master of Science in Data Science that can be completed on-campus or online . Geared toward experienced professionals or recent graduates, the program offers unique features such as studying each course one month at a time for convenience. The curriculum is across 13 courses with 58.5 units, and students learn abilities such as data management and machine learning methods, creating and analyzing data files, and developing team productivity to research and improve company performance.

Requirements and what you could do

The program concludes with a three-month capstone project and has a requirement of students receiving a cumulative 3.0 GPA for the previous courses. Students will either work with real data from sponsored companies or other university-approved public data to analyze problems and develop solutions, showcasing the skills they have learned in their education.

Stanford University: Foundations of Data Science Certificate

For those needing quick statistics and programming education, the Stanford School of Engineering offers a Foundations of Data Science certification. There are only three courses needed to complete curriculum, including an introduction to statistics and a deep dive into Python and R programming. The entire program will take around 30 to 40 hours to complete and is entirely self-paced for up to 90 days after enrollment. There is no requirement to have prior experience before joining and no final exams or capstone projects to complete the certificate.

Campus Based Data Science Programs in California

Msds program at the university of san francisco, data scholarship opportunities within california.

A couple of scholarships are available for data science graduates entering the University of California-Berkeley. The Jack Larson Data for Good Fellowship offers an $8,500 award for those completing a Master of Information in Data Science degree and they must show how they are using the education to create a better life and society. Another scholarship for MIDS students that can demonstrate financial need waives the week-long residency fee of $500.

Women in STEM

For women that are members of the IEEE (Institute of Electrical and Electronics Engineers) Women in Engineering for at least a year, they are eligible for a scholarship from the organization if they are enrolled in the MIDS program at UC-Berkeley. The award is up to $7,500 toward tuition.

Students working in the Master of Science in Data Science program at the University of San Francisco are automatically entered into a university-sponsored scholarship that is between a $2,000 and $10,000 award. Those with high academic marks will be considered.

Data Science Events, Meetups, and Conferences in California

Datax san francisco.

Another summit, AI in Marketing, collects various high-level marketers and data scientists from a wide variety of companies like Uber, Instacart, and GoDaddy. Attendees will learn how AI helps bring in customers and keeps them using products and services, as well as learning the latest disruptive technology.

Big Data Science

Boasting with over 5,000 members, one of the biggest monthly meetups is the Big Data Science group in Fremont. Every fourth Sunday of the month, content involves general information around AI, machine learning, and the internet of the things, along with interactive experience with using software tools. Students of all levels in data science are welcome to join.

Parents are welcome to join younger students, but only one as meetings are limited in size. Location of the meetings vary and other in-depth topics they have covered are chatbots, blockchain, and automation.

Data Science Careers in California

When it comes to opportunities in the tech industry, it is no surprise that as of 2021, California leads the way with over 1,880,000 jobs and is the fastest-growing state in the country according to CompTIA .

Only the state of Washington comes close to their level of employment in STEM along the Western portion of the United States.

Aside from Silicon Valley, there are other cities in California for data science careers

Of the many popular metro areas in the state, the Bay Area combination of San Francisco, Oakland, San Jose, and Santa Clara has over 425,000 workers compared to the Los Angeles-Long Beach-Anaheim area with over 327,000 opportunities. IT services is the leading industry sector with positive 3.9 percent year-over-year growth.

Because the state is so big, having 9.4 percent of the workforce represent the tech industry is significant. This represents over a $482 billion impact in the economy. The median salary for workers in California sits at $96,237, which is only lower than Washington across the entire country. It is higher than 101 percent of the median national wages.

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Home / Schools By State / Master’s in Data Science Programs in California

If you’re interested in developing competitive data science skills to solve complex challenges in business or elsewhere, you might be considering a master’s in data science. It’s important to consider learning in a region — like California — that boasts innovation, where you will have access to people and places that are involved in the field of data science. California offers a wide range of quality programs that are conveniently located and can help you develop the skills you need to pursue your career goals.

Choosing the Best Master’s in Data Science Program in California for You

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University of California, Berkeley

School of information, master of information and data science.

Earn your Master’s in Data Science online from UC Berkeley in as few as 12 months.

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From  developing an AI system to identify pneumonia  to l everaging machine learning to predict the spread of COVID-19 , leaders, researchers and scholars in California are harnessing the power of data science to make the world a better place. But data science isn’t only valuable in the health care sector.

“Data science and artificial intelligence are playing an increasingly important and expansive role in the world today, including the rapid advancement in key research fields, like health care, agriculture, environment and bioengineering,” Thomas Strohmer, professor in the UC Davis Department of Mathematics, told  EurekAlert!, a service of the American Association for the Advancement of Science.

Data science is necessary for the success of organizations across all industries, too, especially business. In June 2020, Citibank launched a strategic advisory group for its clients focused solely on data science. Their goal is “to make data science a stronger part of its corporate finance advice” to further “empower Citi’s bankers to use their judgement with the help of data analytics,” reported the  Institutional Investor.

Here’s everything you need to know about schools, job prospects, online alternatives, graduate scholarships, and networking opportunities. Read through for a comprehensive  list of all the data science programs in California .

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Earn a Master of Information and Cybersecurity online from UC Berkeley’s School of Information. Complete your degree in 20 months.

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Studying Data Science in California

California, home to  Apple ,  Google ,  Facebook ,  Cisco  and countless startups, is considered a tech hub in the United States, an epicenter of data science innovation. This makes California an appealing region to study and earn a master’s in data science.

These companies have graduates from California schools, like Stanford, Caltech and the University of California (UC) system, among others. Some highlights:

• UCLA and Stanford have been deemed  Centers of Excellence for Big Data Computing . Participating programs were funded to  receive a total of $656 million through 2020 .
• Caltech’s work with  JPL’s Center for Data Science and Technology , UC Riverside’s efforts with NASA’s  Minority University Research and Education Project (MUREP) , and UC San Diego’s investment in the  San Diego Supercomputer Center (SDSC)  are all only-in-California programs that make the state the perfect place to study data science.

Online Data Science Programs in California

Earning a master’s in data science can set you up for success by preparing you to analyze and leverage data to solve complex challenges. With a new set of analytical, critical thinking and communication skills, you’ll be armed with advanced knowledge to pursue careers in data science.

While the skills and tools you’ll learn in a data science master’s program might be complex, the learning experience doesn’t have to be.  Online degree programs are growing in popularity  and an online master’s in data science may allow you to earn your degree without compromising your career or other obligations.

Getting an online data science master’s degree means you can earn your degree at your own pace, while still having access to dedicated faculty, mentors and career development resources. Choosing the right program is key. Consider factors like the length of the program, the online experience, and faculty.

More than 30 universities across the United States offer online master’s degrees in data science. California offers several, including the University of California system, which offers some of the top data science programs.

Learn more about what to  look for in an online data science program  by visiting our Online Data Science Masters Degrees page.

Online Data Science Master’s in California

Thanks to the UC system, California boasts a wide range of online master’s in data science programs. This selection, present across the board at UC schools statewide, is something of a recent phenomenon.

In 2017, the San Francisco Chronicle reported that, due to global demand for data science degrees,  more schools in the UC system had started adding online programs in the field . It signaled a growing desire for flexible and accessible online master’s in data science — one highlight includes UC Riverside’s data science specialization, added to its online Master of Science in Engineering in 2016.

University of California, Riverside’s online specialization in data science was supported by MUREP’s Fellowships and Internships in Extremely Large Data Sets (FIELDS) grant and jointly developed by UCR faculty and NASA’s Jet Propulsion Laboratory science staff. The  program launched in 2016 . Those behind the program specifically chose to focus on technical skills rather than research.

As always, we recommend looking at a range of opinions to decide whether an online master’s in data science is the right choice for you.

Online Graduate Certificates in Data Science

Another way to develop your skills in data science is to earn an  online graduate certificate in data science, which can be a more flexible, cost-effective option.  In California, you can find short, skills-focused certificate programs through various academic institutions. Stanford feels comfortable with online certificates, which is good news if you want a California name to burnish your résumé.

The programs are often focused on data analysts, new data scientists or mid-level professionals aiming to add needed specializations to their careers. It could help you land that first job, get the promotion you’ve been looking for, or eventually have the skills needed to pursue more rigorous master’s programs. These certificates also give you the chance to collaborate across disciplines. This is especially true in California, with schools and faculty drawn from a talented pool of entrepreneurs, researchers, and marketers. For example, San Jose State offers its online Certificate in Business Analytics through its business school. Look for your options to increase as distance learning becomes more popular.

Online Data Science Bootcamps in California

If you are in California and interested in breaking into the field of data science or data analytics, consider registering for a bootcamp. A bootcamp is a short-term, intensive introduction that may quickly equip you with the basics of data science, the study of how knowledge can be gleaned from various forms of information, or data analysis, a more practice-minded approach to drawing conclusions from information. Some bootcamps in California focus on data science and others on data analytics, and yet others cover both. Learn more about  data science bootcamps  or  data analytics bootcamps  in California.

Check out our guide to  data science and analytics bootcamps in LA . Our guide to Bay Area bootcamps is coming soon!

S ponsored School

Online data science courses in california.

Individual  online data science courses , outside of full-scale degree programs, are another great way for professionals to gain skills and knowledge needed to succeed. They are offered to students at all levels — beginner, intermediate, and advanced — and generally require you to dedicate at least 80 total hours. You might also find courses tied to certificates that could be available to you for an additional fee. Topics could range from ETL (extract, transform, load) to programming languages like R and Python. There are countless courses available from major, reputable California programs. Check out the websites of schools in the UC system as well as other institutions,  like Stanford , for more information on what online data science courses are available.

Data Science Scholarships in California

We chose to focus on university funding that covers data science degrees, but don’t take this as an exhaustive list of information. Your school’s Graduate Studies Office will have information on general scholarships and fellowships and info on financial options. Here’s an overview of scholarship assistance as you look to pursue your online data science degree:

California State University-Fullerton

• The Extension and International Programs (EIP) Scholarship : If you’re interested in CSUF’s online certificate in analytics or data science, you may wish to apply for this scholarship. It’s given to continuing learning of students in any EIP certificate program. The maximum award is $400.

California State University-San Bernardino

• Graduate Business Grant (GBG) : Graduate students in MBA programs, which include the MBA with a Business Intelligence and Information Technology focus, are eligible for a GBG award. Students must demonstrate financial need and meet eligibility criteria applied to other CSU students who are considered for a State University Grant, including classification as a California resident for tuition- and fee-paying purposes.
• Janice Tillema Memorial Scholarship:  This scholarship is open to full-time undergraduates or graduates. Students must be living within a Citizens Business Bank service area (e.g. Inland Empire, San Gabriel Valley or Orange County) and be enrolled in a business major (e.g. the MBA with a Business Intelligence and Information Technology focus).
• Noel and Amanda Massie Scholarship : Open to undergraduates and graduates in the College of Business and Public Administration, this scholarship is awarded to students who are making progress toward their degree. Graduate students must have a minimum 3.25 GPA.

Claremont Graduate University

• Fletcher Jones Information Science Scholars Fellowship : This fellowship is given to students in the Center for Information Systems and Technology who demonstrate the pioneering spirit, vision and dedication of the late Fletcher Jones (co-founder of Computer Sciences Corporation).

Stanford University

• PhD Fellowships : If you’re thinking about a PhD down the line, Stanford has a number of fellowships for doctoral students, including the Stanford Graduate Fellowship in Science and Engineering (SGF). However,  the Institute for Computational and Mathematical Engineering  does not offer guaranteed financial support for MS students.
• Graduate Fellowships : UC Berkeley offers a large number of graduate fellowships, including fellowships that are open to students focusing on research in science (e.g. biotechnology) and data (e.g. second year fellowships for PhD trainees in  Data Sciences for the 21st Century (DS421) .
• Jack Larson Data for Good Fellowship : This generous fellowship is designed to support MIDS students in pursuit of a career that will allow them to use data science to improve human life and benefit society as a whole.
• School of Information (I School) Fellowships : The I School awards a limited number of merit-based fellowships to domestic and international students in the MIMS and PhD programs. MIMS fellowships cover all or part of the registration fees for the first year of study.

University of California, Davis

• Graduate School of Management (GSM) Scholarships : The GSM, which offers an MBA with a business analytics concentration and an MSBA, distributes a number of awards each year, including the  Working Professional Grant for MSBA applicants .

University of California, San Diego

• Rady School of Management Fellowships : Rady, which offers the MSBA degree, provides a limited number of merit-based fellowships to exceptional students (domestic and international). Students can request the Fellowship Application from the Graduate Admissions office after they receive their official offer of admission.
• Sloan Scholar Fellowship : UCSD also awards PhD fellowships to incoming graduate students in a variety of STEM disciplines, including computer science and engineering.

University of Southern California

• Marshall School of Business PhD Fellowships : Marshall, which administers the PhD in Data Sciences & Operations, offers full financial support (fellowship or assistantship) to selected PhD students for four to five years.
• Viterbi School of Engineering Scholarships : Viterbi, which offers the MSCS in Data Science, offers merit-based scholarships in a number of categories.

University of San Francisco

• MS in Data Science Scholarships : Through the College of Arts & Sciences, the MS in Analytics program awards a limited number of merit-based partial scholarships to incoming students. These scholarships do not require a separate application.

University of the Pacific

• School of Engineering & Computer Science (SoECS) Scholarships : SoECS lists all its internal scholarships on its website, but you should contact the school directly to see if your MS in Analytics applies to any of the categories.

Last updated: May 2020.

Data Science Events in California

California offers a range of events for networking, mentorship and community building opportunities. If you’re a data scientist who has just earned your master’s degree or someone brand new to the field, it might make sense for you to check out these events. There is a wide range — large to small — from informal meetups to larger gatherings, like the Data Science Innovation Summit and the Women in Data Science (WiDS) event at Stanford.

*Due to changes brought about by COVID-19, many 2020 events have been cancelled or postponed to later dates. Check out each event’s website to see their updates.

Data Science Meetups & Communities in California

California has a data science meetup for every group (e.g.  Metis ) and interest you can think of. In a changing world with fewer in-person meetings, many of these groups have listed virtual, online events on their Meetup pages. Beyond this, Facebook and social media have provided plenty of digital hubs for community and connection. Here are a few to check out:

• DS3@UCSD: Data Science Student Society : There are many student groups that foster connection and interdisciplinary collaboration for data scientists on Facebook. One example is this one — out of UCSD. Do a simple search for your school and “data science” and you’ll find other examples.
• Bay Area Women in Machine Learning & Data Science : Founded in 2013, this meetup welcomes anyone who identifies as female, genderqueer or non-binary. Meetups can range from workshops and hack nights to discussions on the state of wage inequality. Right now, they’re offering many online video meetings for members.
• DataKind SF Bay Area Facebook Group : DataKind was launched in 2011 as a community of data scientists driven by the mission to use “data science in the service of humanity.” This page is dedicated to the San Francisco/Bay Area branch of the organization. If you are interested in using your skills to give back, check out this page.
• SF Data Mining (San Francisco, CA) : Organized by Todd Holloway and boasting more than 12,000 members, SF Data Mining may well be the longest-running data meetup in San Francisco. People talk data science, big data, and data visualization. Right now, they are having virtual events, to accommodate the world’s current shelter-in-place reality.

Data Science Conferences & Workshops in California

Major data science conferences abound in California. (Think events like  Strata Data Conference ,  Predictive Analytics World ,  IEEE Conferences ,  SIGKDD ,  The Machine Learning Conference , among others). They tend to migrate around the world, but plenty are based in Silicon Valley or Los Angeles. Here are a few of the major events for data scientists in California:

• Open Data Science Conference (ODSC) West : ODSC is known for having an industry/business focus. Along with training sessions and skills workshops, the conference includes a career fair with a job lounge and plenty of opportunities to network.
• Women in Data Science (WiDS) : Stanford hosts this one-day technical conference. With about 400 attendees from 30 universities and 80 companies (1/3 students and 2/3 industry and academics), it’s an ideal place for networking opportunities. They are hosting regional events right now due to the COVID-19 crisis.

Data Science Jobs in California

You’re in a prime position for job hunting with a degree in data science from a California school. The skills of a  data scientist  are in demand. According to the Bureau of Labor Statistics (BLS),  California has the highest employment level and top pay for computer and information research scientists , which include data scientists. You could be helping to solve business problems, use analytical methods and machine learning to make needed business predictions for a company, or enter academia and work on your own research as you next generation. Earning an advanced degree or certifications in data science can help you upskill and prepare for further opportunities in your career.

Data Scientist Salaries in California

According to data from the O*NET OnLine in 2020,  data scientists made an average $127,310 per year in California .

Data Science Programs in California

Below is a comprehensive list of master’s of data science programs in the state of California (along with closely related programs such as an MS in Analytics and a Master’s in Business Analytics). If you represent a university and would like to contact us about editing any of our listings, or adding new programs, please send an email to [email protected].

Last updated: April 2022

Interested in STEM Careers? 

If you’re looking for information on  career paths that involve STEM , see our guides below:

Data Science and Analytics Careers:

• Data Scientist
• Data Analyst
• Business Analyst

Computer Science, Computer Engineering and Information Careers:

• Computer and Information Research Scientist

Marketing and User Research Careers:

• UX Designer  

Compare Careers and STEM Fields:

• Data Analyst vs. Data Scientist
• Cybersecurity vs. Computer Science

Related Graduate STEM Degrees

• Master’s in Business Analytics
• Master’s in Information Systems
• Master’s in Computer Engineering
• Master’s in Computer Science  
• Master’s in Cybersecurity Programs
• Master’s in Data Analytics for Public Policy
• Data Science MBA Programs
• Master’s in Geospatial Science and Geographic Information Systems
• Master’s in Health Informatics
• Master of Library and Information Science

Related Undergraduate STEM Degrees

• Online Bachelor’s in Data Science
• Sponsored:  Computer Science at Simmons

We found 25 universities in California offering Masters of Data Science programs (and/or closely related programs, like MS in Analytics / Masters in Business Analytics). The university’s website will have the most up to date information on specific programs.

If you represent a university and would like to contact us about editing any of our listings, or adding new programs, please send an email to [email protected].

This page includes information from  O*NET OnLine  by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the  CC BY 4.0 license . O*NET® is a trademark of USDOL/ETA.

Berkeley, California

Designed for data science professionals, the UC Berkeley School of Information’s Master of Information and Data Science (MIDS) prepares students to derive insights from real-world data sets, using the latest tools and analytical methods to interpret and communicate their findings in ways that influence decision-making. The MIDS program features a rigorous, multidisciplinary curriculum focused on problem solving, preparing students to creatively apply methods of data collection, analysis, and presentation to address and solve problems in areas of human interest, government, and business.

Enrollment Type: Full-Time and Part-Time

Length of Program: As few as 12 months

Credits: 27

Admission Requirements:

• Official transcripts
• Two letters of recommendation
• GRE not required

The UC Berkeley School of Information’s online Master of Information and Cybersecurity (MICS) exposes students to the advanced technical, conceptual, and practical skills needed to become leaders in cybersecurity. The MICS curriculum offers a holistic approach to cybersecurity so students develop technical expertise while also gaining an understanding of the behavioral, economic, legal, and ethical concerns that shape security in the digital age. 

Length of Program: As few as 20 months

Data Science

California Polytechnic State University

Orfalea college of business, master of science in business analytics, san luis obispo, california.

Name of Degree: Master of Science in Business Analytics

Enrollment Type: Full-Time

Length of Program: Less than 1 year

Credits: 45

– Undergraduate degree from an accredited college or university – 2.5 GPA – Unofficial/Official transcripts – TOEFL/(Temporarily accepting Duolingo) Score for International Students

California State University at East Bay

Hayward, california.

Length of Program: 1+ years

Credits: 36

• Baccalaureate degre
• GRE or GMAT scores
• Official TOEFL, PTE, IELTS Academic Score Report

California State University Fullerton

Extension and international programs, data science certificate, fullerton, california.

Name of Degree: Data Science Certificate

Enrollment Type: Part-Time

Credits: N/A

• Bachelor’s degree with some college level coursework in statistics or mathematics or have some basic programming experience recommended

Master of Science in Information Systems

Name of Degree: Master of Science in Information Systems

Length of Program: 1 year

Credits: 30

• Undergraduate degree 
• Unofficial/Official transcripts
• TOEFL/IELTS Score for International Students
• Prerequisite courses
• Professional resume/CV
•  2.5 GPA
• GMAT/GRE required

California State University at Long Beach

Applied statistics graduate program, long beach, california.

Name of Degree: Applied Statistics Graduate Program

Length of Program: 2 years

• Undergraduate degree
• Resume 
• Statement of purpose
• Three letters of recommendation

California State University Long Beach

Master of science in applied statistics.

Name of Degree: Master of Science in Applied Statistics

California State University, San Bernardino

Master of business administration, san bernardino, california.

Name of Degree: Master of Business Administration

Credits: 36-42

• Bachelor’s Degree
• Personal Statement
• Letter of Recommendation
• English Proficiency for International Student

Chapman University

Schmid college of science and technology, master of science in computational and data science, irvine, california.

Name of Degree: Master of Science in Computational and Data Science

Length of Program: 2+ years

Credits: 31

• Completed coursework in computer programming, differential equations, probability and statistics
• Statement of intent
• English language test

School of Social Science, Policy & Evaluation

Master of science in applied data science and international studies, claremont, california.

Name of Degree: Master of Science in Applied Data Science and International Studies

Length of Program: 1.5+ years

• English proficiency exam for international applicants

Golden Gate University

San francisco, california.

• Letter of Intent
• TOEFL/IELTS

National University of Singapore

Queenstown, singapore.

Credits: 44

San Diego State University

College of arts and letters, master of science in big data analytics, san diego, california.

Name of Degree: Master of Science in Big Data Analytics

• TOEFL, IELTS, or PTE
• Resume or CV
• One or Two letters of recommendation
• One digital portfolio document

San Jose State University

Certificate in business analytics, san jose, california.

Name of Degree: Certificate in Business Analytics

Credits: 12

• All transcripts from Bachelor’s Degree
• Resume or CV 
• TOEFL Scores for International Applicants

Santa Clara University

Leavey school of business, data sciences and business analytics concentration, santa clara, california.

Name of Degree: Data Sciences and Business Analytics Concentration

Enrollment Type: N/A

Credits: 42

• Bachelor’s degree
• Resume or CV or CV
• Personal statement
• Official TOEFL, PTE, IELTS

Master of Science Information Systems

Name of Degree: Master of Science Information Systems

Credits: 48

School of Humanities and Sciences

Master of science in statistics, stanford, california.

Name of Degree: Master of Science in Statistics

• Two letters of recommendation 

Master's in Health Informatics

Name of Degree: Master’s in Health Informatics

• Official transcripts from all programs attended
• Professional resume or CV
• GRE/GMAT Scores

Master of Science in Computer Science

Name of Degree: Master of Science in Computer Science

• Statement of Intent

Master of Science in Computational and Mathematical Engineering

Name of Degree: Master of Science in Computational and Mathematical Engineering

General CME, Computational Geosciences, Data Science, Imaging Science, Mathematical and Computational Finance

Graduate School of Management

Davis, california.

• Bachelor’s degree
• GMAT or GRE waiver available

Credits: 72

• Transcripts (Unofficial for admission, official for enrollment)
• GMAT or GRE scores General Test
• TOEFL / IELTS (For international, non- native English speaking applicants

Masters Degree in Health Informatics

Name of Degree: Masters Degree in Health Informatics

Credits: 55

• TOEFL/IELTS Score for International Student

University of California, Irvine

Paul merage school of business.

Credits: 52

• Graduate Management Admission Test (GMAT) or Graduate Record Examination (GRE) 
• Official TOEFL, PTE, or IELTS (international applicants)

Division of Continuing Education

Data science certificate program.

Name of Degree: Data Science Certificate Program

Length of Program: Less than 1 year – 1+ years

Credits: 15

• Python programming
• Math and statistics for data science

Certificate in Predictive Analytics

Name of Degree: Certificate in Predictive Analytics

Credits: 16

University of California Los Angeles

Samueli school of engineering, master of science in engineering with certificate of specialization in data science engineering, los angeles, california.

Name of Degree: Master of Science in Engineering with Certificate of Specialization in Data Science Engineering

Length of Program: 24 Months

• Bachelor’s degree in an engineering discipline, mathematics or physics
• 3.0 GPA in last two years of undergraduate work
• GRE test scores, waiver available
• TOEFL/IELTS scores for international students
• Recommendations

University of California San Diego

Jacobs school of engineering, master of advanced study in data science and engineering.

Name of Degree: Master of Advanced Study in Data Science and Engineering

Credits: 38

• Undergraduate degree in Engineering, Math, Physics, or other Science field preferred
• A minimum 3.0 GPA
• Two years of relevant work experience or equivalent post Bachelor’s degree required
• Letters of Recommendation: minimum of two required, three recommended

Rady School of Management

Credits: 50

• Transcripts
• GMAT or GRE scores
• TOEFL, IELTS or PTE Score (for international applicants only)
• More than 5 years of Work experience

Spatial Sciences Institute

Masters in geographic information science and technology.

Name of Degree: Masters in Geographic Information Science and Technology

Enrollment Type: Accelerated

Length of Program: 1.5 years

Credits: 28

• Bachelor’s degree 
• 3.0 GPA 
• Professional experience in field or related technologies.

College of Arts and Sciences

Master of science in data science.

Name of Degree: Master of Science in Data Science

Credits: 35

• Completed coursework in probability and statistics, linear algebra, and computer programming
• GRE/GMAT required, waiver available for experience

Dornsife Spatial Science Institute

Master of science in spatial data science.

Name of Degree: Master of Science in Spatial Data Science

Credits: 32

• Undergraduate degree in STEM or related social science from a regionally-accredited university
• Programming experience or one year of calculus
• English language proficiency for international applicants

University of Southern Maine

Certificate in applied statistics, portland, maine.

Name of Degree: Certificate in Applied Statistics

Length of Program: N/A

Credits: 18

• TOEFL for International Students
• Undergraduate/Graduate Transcripts 
• TOEFL/IELTS (only required for international students)

Master of Science in Systems Architecting and Engineering program

Name of Degree: Master of Science in Systems Architecting and Engineering program

• Professional resume
•  Statement of purpose
• Personal History Essay

Master of Science in Healthcare Decision Analytics

Name of Degree: Master of Science in Healthcare Decision Analytics

Credits: 33

USC Viterbi

Master of science in cyber security engineering.

Name of Degree: Master of Science in Cyber Security Engineering

• Undergraduate degree in STEM or related social science from a regionally- accredited university
• GPA minimum of 3.0

School of Engineering and Computer Science

• Coursework completed in linear algebra, statistics and programming in a high-level language
• 2.65 GPA, 3.0 or higher preferred for competitive applicants
• Statement of interest
• TOEFL or IELTS for international applicants

Best Undergraduate Data Science Programs

A data analytics/science specialty prepares students to use computer programming and statistics to scrutinize data for trends and patterns. These are the top undergraduate computer science programs for data analytics/science. Read the methodology »

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University of California, Berkeley

Berkeley, CA

• #1 in Data Analytics/Science
• #2 in Computer Science  (tie)

The University of California, Berkeley overlooks the San Francisco Bay in Berkeley, Calif. Students at this public school have more than 1,000 groups to get involved in, including more than 60 fraternity and sorority chapters.

(out-of-state)

(fall 2022)

SAT, GPA and More

Massachusetts Institute of Technology

Cambridge, MA

• #2 in Data Analytics/Science
• #1 in Computer Science

Though the Massachusetts Institute of Technology may be best known for its math, science and engineering education, this private research university also offers architecture, humanities, management and social science programs. The school is located in Cambridge, Massachusetts, just across the Charles River from downtown Boston.

Carnegie Mellon University

Pittsburgh, PA

• #3 in Data Analytics/Science

Carnegie Mellon University, a private institution in Pittsburgh, is the country’s only school founded by industrialist and philanthropist Andrew Carnegie. The school specializes in academic areas including engineering, business, computer science and fine arts.

Stanford University

Stanford, CA

• #4 in Data Analytics/Science  (tie)

The sunny campus of Stanford University is located in California’s Bay Area, about 30 miles from San Francisco. The private institution stresses a multidisciplinary combination of teaching, learning, and research, and students have many opportunities to get involved in research projects.

University of Washington

Seattle, WA

• #10 in Computer Science

Located north of downtown Seattle, the University of Washington is one of the oldest public universities on the West Coast. It is also a cutting-edge research institution, receiving significant yearly federal funding, and hosting an annual undergraduate research symposium for students to present their work to the community. The university has a highly ranked School of Medicine, College of Engineering and Michael G. Foster School of Business. Known as a commuter school, the university does not require freshmen to live on campus, but it encourages students who do to conserve energy and recycle. Students can join one of the 950-plus student organizations on campus, including about 70 sororities and fraternities. Nearly three-fourths of UW graduates remain in the state post-graduation.

Georgia Institute of Technology

Atlanta, GA

• #6 in Data Analytics/Science
• #6 in Computer Science  (tie)

Georgia Tech, located in the heart of Atlanta, offers a wide range of student activities. The Georgia Tech Yellow Jackets, an NCAA Division I team, compete in the Atlantic Coast Conference and have a fierce rivalry with the University of Georgia. Since 1961, the football team has been led onto the field at home games by the Ramblin' Wreck, a restored 1930 Model A Ford Sport Coupe. Georgia Tech has a small but vibrant Greek community. Freshmen are offered housing, but aren't required to live on campus. In addition to its campuses in Atlanta and Savannah, Georgia Tech has campuses in France, Ireland, Costa Rica, Singapore and China.

University of Michigan--Ann Arbor

Ann Arbor, MI

• #7 in Data Analytics/Science
• #11 in Computer Science  (tie)

The university boasts of Ann Arbor, only 45 minutes from Detroit, as one of the best college towns in the U.S. Freshmen are guaranteed housing but not required to live on campus. Students can join one of the school’s more than 1,500 student organizations or 62 Greek chapters. Athletics play a central role at Michigan, including the football team’s fierce rivalry with Ohio State. Michigan also offers highly ranked graduate programs, including the Stephen M. Ross School of Business, College of Engineering, Law School and Medical School, in addition to the well-regarded School of Dentistry and Taubman College for Architecture and Urban Planning. The University of Michigan Hospitals and Health Centers is ranked among the top hospitals in the country.

Cornell University

• #8 in Data Analytics/Science

Cornell University, a private school in Ithaca, New York, has 14 colleges and schools. Each admits its own students, though every graduate receives a degree from Cornell University. The university has more than 1,000 student organizations on campus.

Harvard University

• #9 in Data Analytics/Science

Harvard University is a private institution in Cambridge, Massachusetts, just outside of Boston. This Ivy League school is the oldest higher education institution in the country and has the largest endowment of any school in the world.

Columbia University

New York, NY

• #10 in Data Analytics/Science
• #14 in Computer Science  (tie)

Columbia University has three undergraduate schools: Columbia College, The Fu Foundation School of Engineering and Applied Sciences (SEAS), and the School of General Studies. This Ivy League, private school guarantees students housing for all four years on campus in Manhattan’s Morningside Heights neighborhood in New York City.

University of California, San Diego

La Jolla, CA

• #11 in Data Analytics/Science

The University of California, San Diego lies alongside the Pacific Ocean in the La Jolla community of San Diego. The UCSD Tritons compete in more than 20 NCAA Division II sports, mainly in the California Collegiate Athletic Association. The school has hundreds of student organizations, and the university hosts a thriving Greek community. All freshmen are eligible for guaranteed on-campus housing for two years, but they are not required to live on campus. The campus has an aquarium and is home to the Large High Performance Outdoor Shake Table, which tests structures’ ability to withstand simulated earthquakes.

University of Illinois Urbana-Champaign

Champaign, IL

• #12 in Data Analytics/Science
• #5 in Computer Science

The University of Illinois is located in the twin cities of Urbana and Champaign in east-central Illinois, only a few hours from Chicago, Indianapolis and St. Louis. The school's Fighting Illini participate in more than 20 NCAA Division I varsity sports and are part of the Big Ten Conference. The university boasts one of the largest Greek systems in the country, and almost a quarter of the student body is involved. It’s not hard to find something to do on campus with more than 1,600 student organizations, including professional, political and philanthropic clubs. All freshmen are required to live on campus.

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More Schools in this List (Alphabetical)

California Institute of Technology

Pasadena, CA

• in Data Analytics/Science
• in Computer Science

The California Institute of Technology focuses on science and engineering education and has a low student-to-faculty ratio of 3:1. This private institution in Pasadena, California, is actively involved in research projects with grants from NASA, the National Science Foundation and the U.S. Department of Health and Human Services.

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Duke University

Located in Durham, North Carolina, Duke University is a private institution that has liberal arts and engineering programs for undergraduates. The Duke Blue Devils sports teams have a fierce rivalry with the University of North Carolina—Chapel Hill Tar Heels and are best known for their outstanding men's basketball program.

Johns Hopkins University

Baltimore, MD

Johns Hopkins University is a private institution in Baltimore that offers a wide array of academic programs in the arts, humanities, social and natural sciences, and engineering disciplines. The Hopkins Blue Jays men’s lacrosse team is consistently dominant in the NCAA Division I; other sports teams at Hopkins compete at the Division III level.

New York University

New York University’s primary campus is located in the lively Greenwich Village neighborhood of Manhattan. NYU is a true city school, with no borders separating a distinct campus from the streets of the Big Apple. Students are guaranteed housing for all four years in the many residence halls throughout Manhattan, but many upperclassmen choose to live off campus in apartments around the city. NYU has a small but active Greek life with more than 30 fraternity and sorority chapters. There are more than 300 student organizations on campus, such as WNYU, the student radio station which streams online and broadcasts on a local FM channel to the university community.

Princeton University

Princeton, NJ

The ivy-covered campus of Princeton University, a private institution, is located in the quiet town of Princeton, New Jersey. Princeton was the first university to offer a "no loan" policy to financially needy students, giving grants instead of loans to accepted students who need help paying tuition.

Purdue University--Main Campus

West Lafayette, IN

Purdue University's West Lafayette, Indiana, campus is the main campus in the Purdue University system, which encompasses four other campuses throughout the state. About 20% of students are affiliated with Greek life, and Purdue offers a wide range of activities and organizations. Performance groups include the "All American" Marching Band, six jazz bands and two symphony orchestras. The Boilermakers, Purdue’s athletic teams, compete in the Division I Big Ten Conference and are well known for their dominant men’s and women’s basketball teams. The Boilermaker Special, Purdue’s official mascot, is a railroad locomotive cared for and maintained by the student-run Purdue Reamer Club. Although no students are required to live in university housing, about one-third of undergraduates live on campus.

University of California, Los Angeles

Los Angeles, CA

The University of California, Los Angeles is just five miles away from the Pacific Ocean. The public institution offers 5,000 courses, 140 bachelor's degree programs and 97 minors.

University of Maryland, College Park

College Park, MD

Located between Washington, D.C., and Baltimore, the University of Maryland offers students a suburban lifestyle within easy reach of big-city experiences. The flagship campus in College Park, which has its own subway stop on the D.C.-area Metro transit system, is close to the nation's capital. There are more than 800 clubs and organizations on campus, including nearly 60 fraternities and sororities. Freshmen and all other students are not required to live on campus. Students looking for additional activities can visit the university's "SEE UMD" website, which stands for "Student Entertainment Events" and offers movie screenings, comedy shows, lectures and more. Sports also offer yearlong distractions. The Maryland Terrapins compete in the NCAA Division I Big Ten Conference. The mascot, Testudo, is a Diamondback terrapin — a species of turtle that is the official state reptile. One of several Testudo sculptures on campus sits in front of McKeldin Library, and rubbing its nose is thought to bring good luck, particularly before exams.

University of Pennsylvania

Philadelphia, PA

Founded by Benjamin Franklin, the University of Pennsylvania is a private institution in the University City neighborhood of Philadelphia, Pennsylvania. Students can study in one of four schools that grant undergraduate degrees: Arts and Sciences, Nursing, Engineering and Applied Sciences, and Wharton.

University of Texas at Austin

The University of Texas at Austin is one of the largest schools in the nation. It’s divided into 13 schools and colleges, the biggest of which is the College of Liberal Arts. It also has highly ranked graduate programs, including the McCombs School of Business, Cockrell School of Engineering and School of Nursing. Students can participate in more than 1,000 clubs and organizations or in the sizable UT Greek system. The university has several student media outlets, and its sports teams are notorious competitors in the Division I Big 12 Conference. UT also offers hundreds of study abroad programs, with the most popular destinations being Spain, Italy, the United Kingdom, France and China. Freshmen do not have to live on campus.

Master’s in Data Science

This collaborative degree program is jointly owned by Computer Science and Engineering, the Department of Statistics, the School of Information, and the Department of Biostatistics. The Master’s in Data Science is designed to require every student to receive balanced training in statistical skills and computational skills, combining the educational strengths of the four departments. Graduates of this program are expected to understand data representation and analysis at an advanced level.

With the MS in Data Science all students will be able to: identify relevant datasets, apply the appropriate statistical and computational tools to the dataset to answer questions posed by individuals, organizations or governmental agencies, design and evaluate analytical procedures appropriate to the data, and implement these efficiently over large heterogeneous data sets in a multi-computer environment.

The program is administered by the College of LSA, and detailed program and admissions information can be found on their website .

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Already applied?

Imagine working side-by-side with industry leaders in your field of study. Imagine building upon the skills you've learned in the classroom within a family of legendary brands passionate about creating world-class experiences on a global scale. Now, imagine yourself in a paid Disney Internship.

Audience Modeling and Data Science Graduate Intern, Summer 2024

Job summary:.

About the Role and Program

Supporting the Disney Advertising Sales organization within our Disney Entertainment Television segment, the Data & Measurement Science team are the domain authorities in each of the following areas:

Measurement

Addressability

Programmatic

Data-forward business development

We are an outstanding organization made up of Data Scientists, Data Strategists, Analysts and business domain experts. We collaborate with both internal and external teams to understand how we can lead data-driven initiatives in support of the Advertising Sales organization.

What You Will Do

Does this sound like the team for you? We are looking for an intellectually curious individual to join us as an Audience Modeling and Data Science Graduate Intern in The Walt Disney Company’s DET segment, specifically within our Data Strategy organization. In this role, you will be a sophisticated Data Science Intern who will be responsible for the following:

Partnering with senior members of the Data Strategy team to develop knowledge of advertising sales as an industry and resulting datasets that DET applies to develop predictive models and analytical products.

Lead a project end-to-end, in close collaboration with a mentor, and understand how the team’s work contributes to the Ad Sales organization overall.

Attend team workshops, prioritization and update meetings to understand ways of working and actively participate and contribute to cross-functional initiatives.

Perform ad-hoc analysis to support various projects across our Data & Measurement Science team.

Assist in detailing data models, processes, and other initiatives as specified by leadership and peers.

Collaborate with full-time analysts to gain perspective on different aspects of day-to-day projects and responsibilities.

Network with individuals across the Data & Measurement Science organization, as well as the broader Sales teams, to explore areas of opportunity for Data Science in Advertising.

Required Qualifications & Skills

Course or project-based experience using analytical software to manipulate data (SQL and Python preferred).

Course or project-based work using basic data Engineering Concepts (ETL, ELT).

Shown ability to communicate technical concepts to a technical audience.

Highly engaged, ambitious problem solver who is self-motivated and eager to learn.

Eager to collaborate, become part of a team, and lean-in on asking questions from leadership.

• Currently in the process of obtaining a Master’s in Computer Science, Applied Mathematics, Statistics, or other related quantitative field.

Eligibility Requirements & Program Information

Candidates for this opportunity MUST meet all the below requirements:

At the time of application, be enrolled in an accredited college/university taking at least one class in the semester/quarter (spring/fall) prior to participation in the internship program OR currently participating in a Disney College Program or Disney Internship

Be at least 18 years of age

Possess unrestricted work authorization

Have not completed one year of continual employment on a Disney internship or Disney College Program

Additional Information

The approximate dates of this internship are May/June through July/Aug 2024

Able to provide own housing for the duration of the internship program in Santa Monica, CA

Must provide/have reliable transportation to/from work

About Disney Entertainment:

At Disney Corporate you can see how the businesses behind the Company’s powerful brands come together to create the most innovative, far-reaching and admired entertainment company in the world. As a member of a corporate team, you’ll work with world-class leaders driving the strategies that keep The Walt Disney Company at the leading edge of entertainment. See and be seen by other innovative thinkers as you enable the greatest storytellers in the world to create memories for millions of families around the globe.

About The Walt Disney Company:

The Walt Disney Company, together with its subsidiaries and affiliates, is a leading diversified international family entertainment and media enterprise with the following business segments: Disney Entertainment, ESPN, Disney Parks, and Experiences and Products. From humble beginnings as a cartoon studio in the 1920s to its preeminent name in the entertainment industry today, Disney proudly continues its legacy of creating world-class stories and experiences for every member of the family. Disney’s stories, characters and experiences reach consumers and guests from every corner of the globe. With operations in more than 40 countries, our employees and cast members work together to create entertainment experiences that are both universally and locally cherished.

This position is with Disney Advertising Sales, LLC , which is part of a business we call Disney Entertainment .

Disney Advertising Sales, LLC is an equal opportunity employer. Applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, sexual orientation, gender identity, disability, protected veteran status or any other basis prohibited by federal, state or local law. Disney fosters a business culture where ideas and decisions from all people help us grow, innovate, create the best stories and be relevant in a rapidly changing world.

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