Major Requirements

Students majoring in data science must complete a series of foundational lower-division courses their first year, followed by introductory domain area courses their second year, and more advanced and specialized courses in their third and fourth years.

All courses used to satisfy the major requirements must be taken for a letter grade and completed with a C- or better.

Sample Schedules


Data Science Core Courses

course

title

quarter offered

Prerequisites

DSCI 101

Foundations of Data Science I

Fall, Winter, Spring

None

DSCI 102

Foundations of Data Science II

Winter, Spring

DSCI 101

DSCI 311

Principles and Techniques of Data Science

Fall

DSCI 102, CS 211, MATH 252, MATH 342

DSCI 345

Probability and Statistics for Data Science

Fall, Spring

DSCI 102, CS 211, MATH 252, MATH 342

DSCI 372

Machine Learning for Data Science

Winter

DSCI 345, CS 212


Data Science Capstone

For some domains DSCI 411 may be taken in place of one of the four electives by students with a GPA of at least 3.75 over all in all data science degree courses. See specific domain pages for more details.

Course

Title

Quarter Offered

Prerequisites

DSCI 411

Data Science Capstone Project

N/A

N/A


Mathematics Courses

course

title

quarter offered*

Prerequisites

MATH 251

Calculus I

Fall, Winter, Spring, Summer

MATH 112Z or satisfactory placement test score.

MATH 252

Calculus II

Fall, Winter, Spring, Summer

MATH 251

MATH 341

Elementary Linear Algebra I

Fall, Winter, Summer

MATH 252

MATH 342

Elementary Linear Algebra II

Winter, Spring, Summer

MATH 341


Computer Science Courses

course

title

quarter offered*

Prerequisites

CS 210

Computer Science I

Fall, Winter

Math 112Z

CS 211

Computer Science II

Winter, Spring

CS 210

CS 212

Computer Science III

Fall, Spring

CS 211


Ethics Course

course

title

quarter offered*

Prerequisites

PHIL 223

Data Ethics

Winter

NA

*Course schedules are subject to change.


Computational and Inferential Depth

Select three courses from the below list:

course

title

quarter offered*

prerequisites

CS 314

Computer Organization

Fall, Winter

B- or better in CIS 210-212

CS 322

Introduction to Software Engineering

Winter, Spring

B- or better in CIS 210-212

CS 333

Applied Cryptography

Winter

B- or better in CIS 210-212

CS 330

C/C++ & Unix

Winter, Spring

CS 314

CS 415

Operating Systems

Fall, Spring

CS 330

CS 432

Intro to Internet

Fall

CS 330

Math 253

Calculus III

Fall, Winter, Spring, Summer

Math 252

Math 307

Introduction to Proof

Fall, Winter, Spring, Summer

Math 252

Math 458

Introduction to Mathematical Cryptography

Spring

Math 341

Math 461

Introduction to Statistical Methods I

Fall, Winter

Math 253, Math 307

Math 462

Introduction to Statistical Methods II

Winter, Spring

Math 461

Math 463

Introduction to Statistical Methods III

Spring

Math 342, Math 462

DSCI 410

Visualization for Data Science

Winter

DSCI 311

DSCI 410

Introduction to Deep Learning

Winter

DSCI 372 (can be taken corequisite)

DSCI 410

Data Science for Social Justice

Spring

DSCI 311

* Course schedules are subject to change.


Domain Areas

Requirements include two to three courses from the domain core and four courses from the domain electives. See domain pages for more information.


Why Study Data Science?

What’s required for a degree? It’s all summarized in our major map.