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.
Data Science Core Courses
course | title | quarter offered | Prerequisites |
|---|---|---|---|
Foundations of Data Science I | Fall, Winter, Spring | None | |
Foundations of Data Science II | Winter, Spring | DSCI 101 | |
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 |
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 |
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.
- Accounting Analytics
- Biology
- Earth Sciences
- Economics
- Geography
- Linguistics
- Marketing Analytics
- Music Technology
- Physics
- Sociology
Why Study Data Science?
What’s required for a degree? It’s all summarized in our major map.