Aerial View of Berkeley University Campus and San Francisco Bay California USA

University of California Berkeley Online Master of Information and Data Science

Why University of California Berkeley?

The online Master of Information and Data Science offered by University of California Berkeley provides aspiring data scientists with comprehensive training in techniques and approaches at all stages of the data lifecycle. The University of California Berkeley,  a large public research university in Berkeley, California, expects applicants to have a working knowledge of fundamental computer science concepts, including data structures, algorithms and analysis of algorithms, and linear algebra. GRE or GMAT scores may be submitted with your application but are not required. A minimum undergraduate GPA of 3.00  is expected.

Program Snapshot

University NameUniversity of California Berkeley
StateCalifornia GradeA+
Name of DegreeMaster of Information and Data Science
School or Department Administering ProgramInformation School
Cost per credit$2,573
Tuition for Entire Program$69,471
Test RequirementsOptional GRE or GMAT
Minimum GPA3.00
Prerequisite Courses and SkillsWorking knowledge of fundamental computer science concepts including data structures, algorithms and analysis of algorithms, and linear algebra
Campus Visit Required?Required immersion experience
Typical Time to CompleteThree speeds: accelerated in 12 months; general 20 months; slow 32 months
When Can Students Start the Program?January, May or September
Program ConcentrationsNone
Synchronous ClassesYes
Required Courses
  • Introduction to Data Science Programming
  • Research Design and Application for Data and Analysis
  • Statistics for Data Science
  • Fundamentals of Data Engineering
  • Applied Machine Learning
  • Synthetic Capstone Course
Does the Program Include a Capstone?Yes
Does the Program Include a Practicum or Internship?No
Other Features that Make the Program Unique
  • Interactive online activities, hands-on activities
  • Virtual campus where students create profiles and collaborate/socialize outside of class
  • All students get included global membership to WeWork coworking
  • A curriculum that focuses on full data lifecycle, ethics, messy data
  • Multidisciplinary
  • Proximity to Silicon Valley
Program Objectives (quoted directly from the program)
  • Research Design
  • Data Cleansing
  • Data Engineering
  • Data Mining and Exploring
  • Data Visualization
  • Information Ethics and Privacy
  • Statistical Analysis
  • Machine Learning
Program DescriptionThis 27-credit program takes students through all stages of the data science process, from research design to communicating results. Skills and techniques taught are data cleansing, data engineering, data mining, and exploring, data visualization, statistical analysis, and machine learning. A course in Information Ethics and Privacy provides a necessary context for professionals. A synthetic capstone course is required.

What will I Learn?

The Berkeley program is aimed at educating data scientists who can attack problems through the full data lifecycle with ethical and creative approaches. Students follow data through the processes of data cleansing, data engineering, data mining and exploring, data visualization, statistical analysis, and machine learning informed throughout by their developing knowledge of information ethics and privacy. The primary programming language used throughout is Python, and some students may be required to take a Python programming course as three of the required 27 credits.

Students must choose four courses from the following core courses: Introduction to Data Science Programming, Research Design and  Application for Data and Analysis, Statistics for Data Science, Fundamentals of Data Engineering, and Applied Machine Learning. They then choose four courses from a suite of advanced topics, including Experimental and Causal Inference, Behind the Data: Humans and Values, Deep Learning in the Cloud at the Edge, Statistical Methods for Discrete Response, Time Series and Panel Data, Machine Learning at Scale, Natural Language Processing with Deep Learning, and Data Visualization. Students then have an opportunity to apply the skills and knowledge they have learned through a final capstone project exploring a data-intensive problem, working in groups, and using open data sets.

How much will the program cost?

Students finish their degree within 12 months; 20 months; 32 months and pay $2,573 per credit for a total of 27 credits, or just under $70,000.

How does the program fit into my life?

In comparison with other programs, the Berkeley program offers somewhat less flexibility. Students are required to visit campus once during their degree for an immersion learning experience. Some class material is presented at scheduled times, but other materials can be completed on the student’s own schedule. Students can begin the program in January, May, or September. Berkeley offers three different options for a degree completion timeline. Accelerated students can finish the program in 12 months. Most students choose a medium pace, finishing the program in 20 months. Students who choose the slowest timeline finish the program in 32 months.

Because of the project-based, interactive nature of the program, students can expect to need to schedule times to work with classmates or meet with instructors.  All students in the program receive an included global membership in WeWork coworking spaces so that they can complete coursework outside of their homes and/or meet with local classmates at a WeWork location. The virtual campus platform used by Berkeley also helps students take advantage of collaboration opportunities since it enables students to create profiles and socialize outside of class spaces, leading to deeper connections with classmates.


The Berkeley Master of Information and Data Science program brings the expertise of one of the foremost universities in the data science field to working adults wishing to take the next step in their careers. The program offers several innovations to encourage collaboration and creativity in the online learning space, including scheduled synchronous learning, an on-campus immersion experience, included coworking membership, an online space for social interactions, and a curriculum based on interactive activities and group projects.

Aspiring data scientists who prefer to work independently on most of their academic work may not be suited to the Berkeley program, and the high price of the program will likely put it out of reach for many. However, Berkeley’s proximity to Silicon Valley and its recognized high status within the field may make the program worth it for applicants wishing to ensure their employability after graduation.