It's easy to start your application.
Undergraduate Programs
Bachelor of Science in Computer Science + Math
The McKelvey School of Engineering and the College of Arts & Sciences have developed the Computer Science + Math major to capture the intersection of the two complementary studies.
Engineering students who declare this major must fulfill the distribution and other requirements for the Applied Science degree.
Arts & Sciences students who declare this major must fulfill the distribution and other requirements for the AB degree in addition to the specific requirements listed below.
Core Course Requirements* | ||
---|---|---|
CSE 131 | Introduction to Computer Science | 3 |
CSE 247 | Data Structures and Algorithms | 3 |
Math 131 | Calculus I (AP credit may satisfy this requirement) | 3 |
Math 132 | Calculus II (AP credit may satisfy this requirement) | 3 |
Math 233 | Calculus III | 3 |
Math 310 or Math 310W or CSE 240 |
Foundations for Higher Mathematics Foundations for Higher Mathematics with Writing Logic and Discrete Mathematics |
3-4 |
Math 309 | Matrix Algebra | 3 |
or Math 3211 |
Elementary to Intermediate Statistics and Data Analysis
|
3 |
CSE 347 | Analysis of Algorithms | 3 |
*Each of these core courses must be passed with a grade of C- or better.
Electives |
---|
Seven upper-level courses from Math or Computer Science & Engineering can be chosen from the approved lists below, with the following caveats:
|
Biology and Biomedical Sciences
Code | Title | Units |
---|---|---|
Biol 5657 | Biological Neural Computation | 3 |
Biomedical Engineering
Code | Title | Units |
---|---|---|
BME 470 | Mathematics of Imaging Science | 3 |
Computer Science and Engineering Electives
- CSE 217A Introduction to Data Science
- CSE 341T Parallel Algorithms
- CSE 411A AI and Society
- CSE 412A Introduction to Artificial Intelligence
- CSE 416A Analysis of Network Data
- CSE 417T Introduction to Machine Learning
- CSE 427S Cloud Computing with Big Data Applications
- CSE 442T Introduction to Cryptography
- CSE 447T Introduction to Formal Languages and Automata
- CSE 457A Introduction to Visualization
- CSE 468T Introduction to Quantum Computing
- CSE 510A Deep Reinforcement Learning
- CSE 513T Theory of Artificial Intelligence and Machine Learning
- CSE 514A Data Mining
- CSE 515T Bayesian Methods in Machine Learning
- CSE 516A Multiagent Systems
- CSE 517A Machine Learning
- CSE 518A Human-in-the-Loop Computation
- CSE 527A Natural Language Processing
- CSE 531A AI for Health
- CSE 533T Coding and Information Theory for Data Science
- CSE 534A Large-Scale Optimization for Data Science
- CSE 541T Advanced Algorithms
- CSE 543T Algorithms for Nonlinear Optimization
- CSE 544T Special Topics in Computer Science Theory
- CSE 546T Computational Geometry
- CSE 554A Geometric Computing for Biomedicine
- CSE 555T Adversarial AI
- CSE 559A Computer Vision
- CSE 561A Large Language Models
- CSE 581T Approximation Algorithms
- CSE 584A Algorithms for Biosequence Comparison
- CSE 587A Algorithms for Computational Biology
- CSE 659A Advances in Computer Vision
Electrical & Systems Engineering
ESE 4031 | Optimization for Engineered Planning, Decisions and Operations | 3 |
ESE 415 | Optimization | 3 |
ESE 417 | Introduction to Machine Learning and Pattern Classification | 3 |
ESE 427 | Financial Mathematics | 3 |
ESE 429 | Basic Principles of Quantum Optics and Quantum Information | 3 |
ESE 520 | Probability and Stochastic Processes | 3 |
Linguistics
Code | Title | Units |
---|---|---|
Ling 317 | Intro to Computational Linguistics | 3 |
Ling 427 | Computation and Learnability in Linguistic Theory | 3 |
Mathematics Electives
- Math 350 Dynamical Systems and Chaos
- Math 370 Introduction to Combinatorics
- Math 371 Graph Theory
- Math 407 An Introduction to Differential Geometry
- Math 4111 Introduction to Analysis
- Math 4121 Introduction to Lebesque Integration
- Math 4171 Topology I
- Math 420 Experimental Design
- Math 429 Linear Algebra
- Math 430 Modern Algebra
- SDS 434 Survival Analysis
- Math 4351 Number Theory and Cryptography
- Math 439 Linear Statistical Models
- Math 444 Mathematics of Quantum Theory
- Math 449 Numerical Applied Mathematics
- Math 450 Topics in Applied Mathematics
- Math 456 Topics in Financial Mathematics
- SDS 459 Bayesian Statistics
- SDS 460 Multivariable Statistics
- Math 461 Time Series Analysis
- SDS 4601 Statistical Learning
- SDS 462 Mathematical Foundations of Big Data
- Math 470 Special Topics
- Math 475 Statistical Computation
- SDS 493 Probability
- Math 494 Mathematical Statistics
- SDS 495 Stochastic Processes
Additional Departmental Requirements* | |
---|---|
CWP 100 College Writing I | 3 units |
Engr 310 Technical Writing | 3 units |
Natural Sciences electives | 8 units |
Humanities and Social Sciences electives | 18 units |
Total Units | 32 |
All courses taken to meet any of the above requirements (with the exception of the humanities and social sciences electives) cannot be taken on a pass/fail basis.