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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 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 
34 
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 upperlevel 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 HumanintheLoop Computation
 CSE 527A Natural Language Processing
 CSE 531A AI for Health
 CSE 533T Coding and Information Theory for Data Science
 CSE 534A LargeScale 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.