Data Science

University of California, Berkeley

About the Program

Bachelor of Arts (BA)

The Data Science Major degree program combines computational and inferential reasoning to draw conclusions based on data about some aspect of the real world. Data scientists come from all walks of life, all areas of study, and all backgrounds. They share an appreciation for the practical use of mathematical and scientific thinking and the power of computing to understand and solve problems for business, research, and societal impact.

The Data Science Major will equip students to draw sound conclusions from data in context, using knowledge of statistical inference, computational processes, data management strategies, domain knowledge, and theory. Students will learn to carry out analyses of data through the full cycle of the investigative process in scientific and practical contexts. Students will gain an understanding of the human and ethical implications of data analytics and integrate that knowledge in designing and carrying out their work.

The Data Science major requirements include DATA C8  and DATA C100, the core lower-division and upper-division elements of the major, along with courses from each of the following requirement groups:

  • Foundations in Mathematics and Computing
  • Computational and Inferential Depth
  • Modeling, Learning and Decision Making
  • Probability
  • Human Contexts and Ethics
  • Domain Emphasis

All students will select a Domain Emphasis, a cluster of one lower division course and two upper division courses, that brings them into the context of a domain and allows them to build bridges with data science.

Declaring the Major

Students can apply to declare the Data Science major after completing all the lower-division prerequisites (see the Major Requirements tab). For applicants with prerequisites in progress, applications will be reviewed after the grades for all prerequisites are available.

It is necessary for applicants to achieve a minimum prerequisite grade point average (GPA) in order to declare the Data Science major. Information on this GPA and the process to apply for admission to the major can be found on the Declaring the Major web page.

Minor Program

The Minor in Data Science at UC Berkeley aims to provide students with practical knowledge of the methods and techniques of data analysis, as well as the ability to think critically about the construction and implications of data analysis and models. The minor will empower students across the wide array of campus disciplines with a working knowledge of statistics, probability, and computation that allow students not just to participate in data science projects, but to design and carry out rigorous computational and inferential analysis for their field of interest. Check the Data Science Minor program website for details.

VISIT PROGRAM WEBSITE

Major Requirements

In addition to the University, campus, and college requirements listed on the College Requirements tab, students must fulfill the below requirements specific to the major program. Please check the Data Science program website for updates.

General Guidelines

  • All courses taken to fulfill the major requirements below must be taken for letter-graded credit.
  • No more than two upper-division courses can overlap between two majors.
  • A minimum grade point average (GPA) of 2.0 must be maintained in all courses toward the major, and in all upper-division courses toward the major.

Lower Division Prerequisites

DATA C8Foundations of Data Science4
MATH 1ACalculus3-4
or MATH 10A Methods of Mathematics: Calculus, Statistics, and Combinatorics
or MATH 16A Analytic Geometry and Calculus
MATH 1BCalculus4
MATH 54Linear Algebra and Differential Equations4
or STAT 89A Linear Algebra for Data Science
or EECS 16A
EECS 16B
Designing Information Devices and Systems I
and Designing Information Devices and Systems II
or PHYSICS 89 Introduction to Mathematical Physics
COMPSCI 61AThe Structure and Interpretation of Computer Programs4
or COMPSCI 88 Computational Structures in Data Science
or ENGIN 7 Introduction to Computer Programming for Scientists and Engineers
COMPSCI 61BData Structures4

In some cases, students may complete alternative courses to satisfy the above prerequisites. See the lower-division requirements page on the Data Science program website for more details.

Lower Division Requirements

Students will also be required to take one lower division course towards their choice of Domain Emphasis.

Upper Division Requirements

Students will be required to complete 8 unique upper-division courses for a total of 28 or more units from the following requirement categories.

Principles and techniques of data science
DATA C100Principles & Techniques of Data Science4
Computational and Inferential Depth  

Students will be required to take two upper division courses comprising 7 or more units that provide computational and inferential depth beyond that provided in Data 100 and the lower-division courses. 

Choose two courses comprising 7+ units from the following:
ASTRON 128Astronomy Data Science Laboratory4
COMPSCI 161Computer Security4
COMPSCI 162Operating Systems and System Programming4
COMPSCI 164Programming Languages and Compilers4
COMPSCI 168Introduction to the Internet: Architecture and Protocols4
COMPSCI 169Software Engineering4
or COMPSCI 169A Introduction to Software Engineering
or COMPSCI W169A Software Engineering
COMPSCI 170Efficient Algorithms and Intractable Problems4
COMPSCI 186Introduction to Database Systems4
or COMPSCI W186 Introduction to Database Systems
COMPSCI 188Introduction to Artificial Intelligence4
DATA 144Data Mining and Analytics3
ECON 140Economic Statistics and Econometrics4
or ECON 141 Econometric Analysis
EECS 127Optimization Models in Engineering4
EL ENG 120Signals and Systems4
EL ENG 123Digital Signal Processing4
ENVECON C118Introductory Applied Econometrics4
ESPM 174Design and Analysis of Ecological Research4
IAS C118Introductory Applied Econometrics4
IND ENG 115Industrial and Commercial Data Systems3
IND ENG 135Applied Data Science with Venture Applications3
IND ENG 165Engineering Statistics, Quality Control, and Forecasting4
IND ENG 173Introduction to Stochastic Processes3
INFO 154Data Mining and Analytics3
INFO 159Natural Language Processing4
INFO 190Special Topics in Information (Introduction to Data Visualization - only when offered on this topic)4
NUC ENG 175Methods of Risk Analysis3
PHYSICS 188Bayesian Data Analysis and Machine Learning for Physical Sciences (previously PHYSICS 188)4
STAT 135Concepts of Statistics4
STAT 150Stochastic Processes3
STAT 151ALinear Modelling: Theory and Applications4
STAT 152Sampling Surveys4
STAT 153Introduction to Time Series4
STAT 158The Design and Analysis of Experiments4
STAT 159Reproducible and Collaborative Statistical Data Science4
UGBA 147Special Topics in Operations and Information Technology Management (Advanced Business Analytics - only when offered on this topic)1-4
Probability

Students will be required to take one upper-division course on probability. 

Choose one of the following:
EL ENG 126Probability and Random Processes4
IND ENG 172Probability and Risk Analysis for Engineers4
STAT 134Concepts of Probability4
STAT 140Probability for Data Science4
Modeling, Learning, and Decision-Making

Students will be required to take one upper-division course on modeling, learning, and decision-making.

Choose one of the following:
COMPSCI 182Designing, Visualizing and Understanding Deep Neural Networks4
COMPSCI L182Designing, Visualizing and Understanding Deep Neural Networks4
COMPSCI W182Designing, Visualizing and Understanding Deep Neural Networks4
COMPSCI 189Introduction to Machine Learning4
DATA C102Data, Inference, and Decisions4
IND ENG 142Introduction to Machine Learning and Data Analytics3
STAT 154Modern Statistical Prediction and Machine Learning4
Human Contexts and Ethics

Students will be required to take one course from a curated list of courses that establish a human, social, and ethical context in which data analytics and computational inference play a central role. 

AFRICAM 134Information Technology and Society4
or AFRICAM/AMERSTD C134 Information Technology and Society
BIO ENG 100Ethics in Science and Engineering3
CY PLAN 101Introduction to Urban Data Analytics4
DATA C104Human Contexts and Ethics of Data - DATA/History/STS4
INFO 188Behind the Data: Humans and Values3
ISF 100JThe Social Life of Computing4
NWMEDIA 151ACTransforming Tech: Issues and Interventions in STEM and Silicon Valley4
PHILOS 121Moral Questions of Data Science4
PB HLTH C160/ESPM C167Environmental Health and Development4
Domain Emphasis

Students will also be required to take two upper division courses towards their choice of Domain Emphasis.

Domain Emphases that students can choose from:

Minor Requirements

The Minor in Data Science at UC Berkeley aims to provide students with practical knowledge of the methods and techniques of data analysis, as well as the ability to think critically about the construction and implications of data analysis and models. The minor will empower students across the wide array of campus disciplines with a working knowledge of statistics, probability, and computation that allow students not just to participate in data science projects, but to design and carry out rigorous computational and inferential analysis for their field of interest.

General Guidelines

  1. All minors must be declared no later than one semester before a student's Expected Graduation Term (EGT). If the semester before EGT is fall or spring, the deadline is the last day of RRR week. If the semester before EGT is summer, the deadline is the final Friday of Summer Sessions. For more information about declaring the minor, view the Data Science minor webpage.

  2. All courses for the minor must be taken for a letter grade.

  3. Students must earn a C- or better in each course, and have a minimum 2.0 GPA in all courses towards the minor.

  4. Students may overlap up to 1 course in the upper division requirements for the Data Science minor with each of their majors (for example, a Computer Science major may count COMPSCI/DATA/STAT C100 toward both their major and the Data Science minor).

  5. A maximum of one course offered by or cross-listed with the student’s major department(s) may count toward the data science minor upper-division requirements, including any overlapping course (for example, if a Computer Science major takes COMPSCI/DATA/STAT C100 toward the Data Science minor, this is the only COMPSCI, ELENG, or EECS course which may count toward the upper-division requirements for the minor).

  6. An upper-division course used to fulfill a lower-division requirement (for example, Stat 134 to fulfill the probability requirement) will not be counted toward the maximum 1 course allowed to overlap with the major, nor will it fulfill one of the four upper division course requirements.

  7. There is no restriction on overlap with another minor.

  8. Courses used to fulfill the minor requirements may be applied toward the Seven-Course Breadth requirement, for Letters & Science students.

  9. All minor requirements must be completed prior to the last day of finals during the semester in which you plan to graduate.

Lower-division Requirements

DATA C8Foundations of Data Science4
COMPSCI 88Computational Structures in Data Science3-4
or COMPSCI 61A The Structure and Interpretation of Computer Programs
or ENGIN 7 Introduction to Computer Programming for Scientists and Engineers
Choose one of the following: 1
STAT 88Probability and Mathematical Statistics in Data Science3-4
or COMPSCI 70 Discrete Mathematics and Probability Theory
or MATH 10B Methods of Mathematics: Calculus, Statistics, and Combinatorics
or MATH 55 Discrete Mathematics

Upper-division Requirements

Complete a total of 4 upper-division courses in one of the following pathways:

Data 100 Pathway
DATA C100Principles & Techniques of Data Science4
Choose one of the following:
Information Technology and Society [4]
Information Technology and Society
Ethics in Science and Engineering [3]
Introduction to Urban Data Analytics [4]
Human Contexts and Ethics of Data - DATA/History/STS [4]
Theory and Method in the Digital Humanities [3]
Environmental Health and Development [4]
Behind the Data: Humans and Values [3]
The Social Life of Computing [4]
Moral Questions of Data Science [4]

Choose TWO from the Approved Elective List.

Statistics PATHWAY
STAT 131AStatistical Methods for Data Science4
STAT 133Concepts in Computing with Data3
Choose one of the following:
Information Technology and Society [4]
Information Technology and Society
Ethics in Science and Engineering [3]
Introduction to Urban Data Analytics [4]
Human Contexts and Ethics of Data - DATA/History/STS [4]
Theory and Method in the Digital Humanities [3]
Environmental Health and Development [4]
Behind the Data: Humans and Values [3]
The Social Life of Computing [4]
Moral Questions of Data Science [4]

Choose ONE from the Approved Elective List.

 

College Requirements

Undergraduate students must fulfill the following requirements in addition to those required by their major program.

For detailed lists of courses that fulfill college requirements, please review the College of Letters & Sciences page in this Guide. For College advising appointments, please visit the L&S Advising Pages. 

University of California Requirements

Entry Level Writing

All students who will enter the University of California as freshmen must demonstrate their command of the English language by fulfilling the Entry Level Writing requirement. Fulfillment of this requirement is also a prerequisite to enrollment in all reading and composition courses at UC Berkeley. 

American History and American Institutions

The American History and Institutions requirements are based on the principle that a US resident graduated from an American university, should have an understanding of the history and governmental institutions of the United States.

Berkeley Campus Requirement

American Cultures

All undergraduate students at Cal need to take and pass this course in order to graduate. The requirement offers an exciting intellectual environment centered on the study of race, ethnicity and culture of the United States. AC courses offer students opportunities to be part of research-led, highly accomplished teaching environments, grappling with the complexity of American Culture.

College of Letters & Science Essential Skills Requirements

Quantitative Reasoning

The Quantitative Reasoning requirement is designed to ensure that students graduate with basic understanding and competency in math, statistics, or computer science. The requirement may be satisfied by exam or by taking an approved course.

Foreign Language

The Foreign Language requirement may be satisfied by demonstrating proficiency in reading comprehension, writing, and conversation in a foreign language equivalent to the second semester college level, either by passing an exam or by completing approved course work.

Reading and Composition

In order to provide a solid foundation in reading, writing, and critical thinking the College requires two semesters of lower division work in composition in sequence. Students must complete parts A & B reading and composition courses by the end of their second semester and a second-level course by the end of their fourth semester.

College of Letters & Science 7 Course Breadth Requirements

Breadth Requirements

The undergraduate breadth requirements provide Berkeley students with a rich and varied educational experience outside of their major program. As the foundation of a liberal arts education, breadth courses give students a view into the intellectual life of the University while introducing them to a multitude of perspectives and approaches to research and scholarship. Engaging students in new disciplines and with peers from other majors, the breadth experience strengthens interdisciplinary connections and context that prepares Berkeley graduates to understand and solve the complex issues of their day.

Unit Requirements

  • 120 total units

  • Of the 120 units, 36 must be upper division units

  • Of the 36 upper division units, 6 must be taken in courses offered outside your major department
Residence Requirements

For units to be considered in "residence," you must be registered in courses on the Berkeley campus as a student in the College of Letters & Science. Most students automatically fulfill the residence requirement by attending classes here for four years. In general, there is no need to be concerned about this requirement, unless you go abroad for a semester or year or want to take courses at another institution or through UC Extension during your senior year. In these cases, you should make an appointment to meet an adviser to determine how you can meet the Senior Residence Requirement.

Note: Courses taken through UC Extension do not count toward residence.

Senior Residence Requirement

After you become a senior (with 90 semester units earned toward your BA degree), you must complete at least 24 of the remaining 30 units in residence in at least two semesters. To count as residence, a semester must consist of at least 6 passed units. Intercampus Visitor, EAP, and UC Berkeley-Washington Program (UCDC) units are excluded.

You may use a Berkeley Summer Session to satisfy one semester of the Senior Residence requirement, provided that you successfully complete 6 units of course work in the Summer Session and that you have been enrolled previously in the college.

Modified Senior Residence Requirement

Participants in the UC Education Abroad Program (EAP), Berkeley Summer Abroad, or the UC Berkeley Washington Program (UCDC) may meet a Modified Senior Residence requirement by completing 24 (excluding EAP) of their final 60 semester units in residence. At least 12 of these 24 units must be completed after you have completed 90 units.

Upper Division Residence Requirement

You must complete in residence a minimum of 18 units of upper division courses (excluding UCEAP units), 12 of which must satisfy the requirements for your major.

Plans of Study

Sample plans for completing major coursework are included below. These are not comprehensive plans which will reflect the situation of every student. These sample plans are meant only to serve as a baseline guide for structuring a plan of study, and only include the minimum courses for meeting the L&S Data Science major requirements. 

For new freshmen (four-year plan):
Freshman
FallUnitsSpringUnits
DATA C84COMPSCI 61A or 883-4
MATH 1A (10A or 16A acceptable)4MATH 1B4
Reading & Composition A4Reading & Composition B4
DATA 88 (optional)2Non-major Elective1-2
 14 12-14
Sophomore
FallUnitsSpringUnits
COMPSCI 61B4MATH 54 or STAT 89A4
Breadth/Elective3-4Lower-division Domain Emphasis3-4
Breadth/Elective3-4Breadth/Elective3-4
 10-12 10-12
Junior
FallUnitsSpringUnits
DATA C1004Computational & Inferential Depth #13-4
Probability (e.g. Stat 140)4Upper-division Domain Emphasis #13-4
Breadth/Elective3-4Breadth/Elective3-4
 11-12 9-12
Senior
FallUnitsSpringUnits
Computational & Inferential Depth #23-4Modeling, Learning & Decision Making (e.g. Data 102)4
Upper-division Domain Emphasis #23-4Human Contexts & Ethics (e.g. Data 104)3-4
Breadth/Elective3-4Breadth/Elective3-4
 9-12 10-12
Total Units: 85-100
For transfer students (two-year plan):

*Note: this sample plan is based on a transfer student who has completed 1 year of  calculus, linear algebra and data structures, as well as IGETC/L&S 7-Course Breadth at their previous college or university, which may not reflect the reality for every transfer student. Students should consult with a Data Science Advisor to make an individualized plan based on their specific situation. 

First Year
FallUnitsSpringUnits
DATA C84DATA C1004
COMPSCI 88 or 61A3-4Probability (e.g. Stat 140)4
Lower-division Domain Emphasis2-4American Cultures/Upper-division Outside Major3-4
Non-major Elective1-2Non-major Elective1-2
 10-14 12-14
Second Year
FallUnitsSpringUnits
Computational & Inferential Depth #13-4Computational & Inferential Depth #23-4
Upper-division Domain Emphasis #13-4Modeling, Learning & Decision Making (e.g. Data 102)3-4
Upper-division Domain Emphasis #23-4Human Contexts & Ethics (e.g. Data 104)3-4
Non-major Elective1-2Non-major Elective1-2
 10-14 10-14
Total Units: 42-56

Major Map

Major Maps help undergraduate students discover academic, co-curricular, and discovery opportunities at UC Berkeley based on intended major or field of interest. Developed by the Division of Undergraduate Education in collaboration with academic departments, these experience maps will help you:

  • Explore your major and gain a better understanding of your field of study

  • Connect with people and programs that inspire and sustain your creativity, drive, curiosity and success

  • Discover opportunities for independent inquiry, enterprise, and creative expression

  • Engage locally and globally to broaden your perspectives and change the world

  • Reflect on your academic career and prepare for life after Berkeley

Use the major map below as a guide to planning your undergraduate journey and designing your own unique Berkeley experience.

View the Data Science Major Map PDF.

Academic Opportunities

Student Teams

Each semester, we recruit dozens of students to participate in our student teams as interns and volunteers. Teams include Communications, Analytics, External Relations, and Curriculum Development.  Interested students can email ds-teams@berkeley.edu with questions about the opportunities. Learn more here.

Data Scholars

The Data Scholars program addresses issues of underrepresentation in the data science community by establishing a welcoming, educational, and empowering environment for underrepresented and nontraditional students. The program, which offers specialized tutoring, advising, mentorship, and workshops, is especially suited for students who can bring diverse perspectives to the field of Data Science. Learn more here.

Data Peer Consulting

Students in our consulting network help make data science accessible across the broader campus community by providing technical support and tutoring. Peer consultants are available at Moffitt Library on a drop-in basis. Learn more here.

Data Science Peer Advising

Academic Peer Advisors are available to help fellow students choose classes, explore academic interests, and learn how to declare the Data Science major. The Peer Advising services are available on a drop-in basis at Moffitt Library. Contact the Data Science Peer Advisors at ds-peer-advising@berkeley.edu. Learn more here.

Discovery Research Program

The Data Science Discovery Research program connects undergraduates with hands-on, team-based opportunities to contribute to cutting-edge research projects with graduate and post-doctoral students, community impact groups, entrepreneurial ventures, and educational initiatives across UC Berkeley. Learn more here.

Data Science Nexus

The Data Science Nexus is an alliance of data science student organizations on campus that work together to build community, host industry events, and provide academic support for students. In recognition of the extraordinarily diverse and multi-faceted nature of data science, members of the Nexus come from a variety of domains. Learn more here.

Related Courses

Contact Information

Data Science Education Program; Division of Computing, Data Science, and Society

Hearst Field Annex, B

VISIT PROGRAM WEBSITE

Associate Provost and Dean

Jennifer Tour Chayes

Associate Dean for Undergraduate Education

Deborah Nolan

Director of Advising

Laura Imai

436 Evans Hall

ds-advising@berkeley.edu

Undergraduate Major Advisor

Marjorie Ensor

442 Evans Hall

ds-advising@berkeley.edu

Undergraduate Major Advisor

Aaron Giacosa

442 Evans Hall

ds-advising@berkeley.edu

Undergraduate Major Advisor

Amanda Dillon

442 Evans Hall

ds-advising@berkeley.edu

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