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About the ProgramBachelor 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 includeDATAC8andDATAC100, the core lower-division and upper-division elements of the major, along with courses from each of the following requirement groups:

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 themto build bridges with data science.

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 toachieve 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.

TheMinor in Data Scienceat 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 websitefor details.

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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 theData Science program websitefor updates.

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.

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

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

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 100and the lower-division courses.

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

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

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.

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

Domain Emphases that students can choose from:

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.

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.

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

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

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).

A maximum of one course offered by or cross-listed with the students 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).

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.

There is no restriction on overlap with another minor.

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

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

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

Choose ONE from theApproved Elective List.

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 theCollege of Letters & Sciencespage in this Guide. For College advising appointments, please visit the L&S Advising Pages.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

L&S College Requirements: Reading & Composition, Quantitative Reasoning, and Foreign Language, which typically must be satisfied with a letter grade, can be satisfied with a Passed (P) grade during Fall 2020 and Spring 2021 if a student elects to take the course for P/NP. Note: This doesnotinclude Entry Level Writing (College Writing R1A).

Requirements within L&S majors and minors can be satisfied with Passed (P) grades during the Fall 2020 and Spring 2021 semesters. This includes prerequisites for majors. Contact your intended or declaredmajor/minor adviserfor more details.

Departments may create alternative methods for admitting students into their majors.

L&S students will not be placed on academic probation automatically for taking all of their courses P/NP during Fall 2020 or Spring 2021.

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.

*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.

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

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.

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.

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.

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 morehere.

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.

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.

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.

Expand all course descriptions [+]Collapse all course descriptions [-]

Terms offered: Spring 2021This course engages students with fundamental questions of justice in relation to data and computing in American society. Data collection, visualization, and analysis have been entangled in the struggle for racial and social justice because they can make injustice visible, imaginable, and thus actionable. Data has also been used to oppress minoritized communities and institutionalize, rationalize, and naturalize systems of racial violence. The course examines key sites of justice involving data (such as citizenship, policing, prisons, environment, and health). Along with critical social science tools, students gain introductory experience and do collaborative and creative projects with data science using real-world data.Data and Justice: Read More [+]

Hours & Format

Fall and/or spring: 15 weeks - 3 hours of lecture and 1.5 hours of discussion per week

Additional Details

Subject/Course Level: Data Science, Undergraduate/Undergraduate

Grading/Final exam status: Letter grade. Alternative to final exam.

Data and Justice: Read Less [-]

Terms offered: Prior to 2007An introduction to computational thinking and quantitative reasoning, preparing students for further coursework, especially Foundations of Data Science (CS/Info/Stat C8). Emphasizes the use of computation to gain insight about quantitative problems with real data. Expressions, data types, collections, and tables in Python. Programming practices, abstraction, and iteration. Visualizing univariate and bivariate data with bar charts, histograms, plots, and maps. Introduction to statistical concepts including averages and distributions, predicting one variable from another, association and causality, probability and probabilistic simulation. Relationship between numerical functions and graphs. Sampling and introduction to inference.Introduction to Computational Thinking with Data: Read More [+]

Objectives & Outcomes

Course Objectives: C6 also includes quantitative reasoning concepts that arent covered in Data 8. These include certain topics in: principles of data visualization; simulation of random processes; and understanding numerical functions through their graphs. This will help prepare students for computational and quantitative courses other than Data 8.C6 takes advantage of the complementarity of computing and quantitative reasoning to enliven abstract ideas and build students confidence in their ability to solve real problems with quantitative tools. Students learn computer science concepts and immediately apply them to plot functions, visualize data, and simulate random events.

Foundations of Data Science (CS/Info/Stat C8, a.k.a. Data 8) is an increasingly popular class for entering students at Berkeley. Data 8 builds students computing skills in the first month of the semester, and students rely on these skills as the course progresses. For some students, particularly those with little prior exposure to computing, developing these skills benefits from further time and practice. C6 is a rapid introduction to Python programming, visualization, and data analysis, which will prepare students for success in Data 8.

Student Learning Outcomes: Students will be able to perform basic computations in Python, including working with tabular data.Students will be able to understand basic probabilistic simulations.Students will be able to understand the syntactic structure of Python code.Students will be able to use good practices in Python programming.Students will be able to use visualizations to understand univariate data and to identify associations or causal relationships in bivariate data.

Hours & Format

Summer: 6 weeks - 4 hours of lecture, 2 hours of discussion, and 4 hours of laboratory per week

Additional Details

Subject/Course Level: Data Science, Undergraduate/Undergraduate

Grading/Final exam status: Letter grade. Final exam required.

Formerly known as: Computer Science C8R/Statistics C8R

Also listed as: COMPSCIC6/STATC6

Introduction to Computational Thinking with Data: Read Less [-]

Terms offered: Summer 2021 8 Week Session, Spring 2021, Fall 2020, Summer 2020 8 Week SessionFoundations of data science from three perspectives: inferential thinking, computational thinking, and real-world relevance. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social and legal issues surrounding data analysis, including issues of privacy and data ownership.Foundations of Data Science: Read More [+]

Rules & Requirements

Prerequisites: This course may be taken on its own, but students are encouraged to take it concurrently with a data science connector course (numbered 88 in a range of departments)

Credit Restrictions: Students will receive no credit for DATAC8COMPSCIC8INFOC8STATC8 after completing COMPSCI 8, or DATA 8. A deficient grade in DATAC8COMPSCIC8INFOC8STATC8 may be removed by taking COMPSCI 8, COMPSCI 8, or DATA 8.

Hours & Format

Fall and/or spring: 15 weeks - 3-3 hours of lecture and 2-2 hours of laboratory per week

Summer: 8 weeks - 6 hours of lecture and 4 hours of laboratory per week

Additional Details

Subject/Course Level: Data Science, Undergraduate/Undergraduate

Grading/Final exam status: Letter grade. Final exam required.

Formerly known as: Computer Science C8/Statistics C8/Information C8

Also listed as: COMPSCIC8/INFOC8/STATC8

Foundations of Data Science: Read Less [-]

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Data Science < University of California, Berkeley