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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 240 | Logic and Discrete Mathematics | 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 |
Foundations for Higher Mathematics Foundations for Higher Mathematics with Writing |
3 |
| Math 309 | Matrix Algebra | 3 |
|
or ESE 326 or SDS 3211 |
Elementary to Intermediate Statistics and Data Analysis Probability and Statistics for Engineering Statistics for Data Science I |
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:
|
Computer Science and Engineering
- CSE 217A Introduction to Data Science (or BME 440 Biomedical Data Science)
- CSE 341T Parallel Algorithms
- CSE 4061 Text Mining
- 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
Biology and Biomedical Sciences
- Biol 5657 Biological Neural Computation
Electrical & Systems Engineering
- ESE 4031 Optimization for Engineered Planning, Decisions and Operations
- ESE 415 Optimization
- ESE 417 Introduction to Machine Learning and Pattern Classification
- ESE 427 Financial Mathematics
- ESE 429 Basic Principles of Quantum Optics and Quantum Information
- ESE 520 Probability and Stochastics Processes
Biomedical Engineering
Statistics and Data Science
- SDS 420 Experimental Design
- SDS 434 Survival Analysis
- SDS 439 Linear Statistical Models
- SDS 459 Bayesian Statistics
- SDS 460 Multivariate Statistical Analysis
- SDS 461 Time Series Analysis
- SDS 462 Mathematical Foundations of Big Data
- SDS 475 Statistical Computation
- SDS 493 Probability
- SDS 495 Stochastic Processes
Mathematics
- Math 350 Dynamical Systems in 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 429 Linear Algebra
- Math 430 Modern Algebra
- Math 4351 Number Theory and Cryptography
- Math 444 The Mathematics of Quantum Theory
- Math 449 Numerical Applied Mathematics
- Math 450 Topics in Applied Mathematics
- Math 456 Topics in Financial Mathematics
- Math 470 Topics in Graph Theory
- Math 494 Mathematical Statistics
- Math 535 Statistical Learning: An Introduction to Data Mining
Linguistics
Physics
- Physics 427 Introduction to Computational Physics
| 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 |
*The College Writing and Humanities and Social Sciences requirements are those required of all students in the McKelvey School of Engineering. The Natural Sciences requirement is for 8 units designated NSM (Natural Sciences and Mathematics) from any of the following departments: Anthropology; Biology; Chemistry; Earth, Environmental, and Planetary Sciences; Environmental Studies or Physics. The College Writing and Natural Sciences courses must be completed with a grade of C- or better.
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.