The Computing, Mathematics, and Analytics Specialization is intended for students aiming at graduate work in the theory of computing or in an applied area of computing that requires significant mathematical expertise, such as communications, optimization, security, or biomedical computing. This program will give students a potent combination of computer science and mathematics as it relates to research in Computing, and will prepare graduates well for advanced degrees or careers in a variety of areas in industry.
Program Requirements
The following are the requirements for the Computing, Mathematics, and Analytics Specialization. This information is meant as a guide and is subject to change. The precise and up-to-date requirements for Computing degrees can be found online in the University's Academic Calendar. In case of discrepancies, please notify the School's Curriculum Coordinator.
A half-year/one-term course is worth 3.0 units, while a full-year/two-term course is worth 6.0 units.
1. Core
Code | Title | Units |
---|---|---|
Computing: | ||
A. Complete the following: | ||
CISC 121 | Introduction to Computing Science I | 3.0 |
CISC 124 | Introduction to Computing Science II | 3.0 |
B. Complete the following: | ||
CISC 203 | Discrete Mathematics for Computing II | 3.0 |
CISC 204 | Logic for Computing Science | 3.0 |
CISC 221 | Computer Architecture | 3.0 |
CISC 223 | Software Specifications | 3.0 |
CISC 235 | Data Structures | 3.0 |
C. Complete 3.0 units from the following: | 3.0 | |
CISC 322 | Software Architecture | |
CISC 326 | Game Architecture | |
D. Complete the following: | ||
CISC 324 | Operating Systems | 3.0 |
CISC 360 | Programming Paradigms | 3.0 |
CISC 365 | Algorithms I | 3.0 |
E. Complete the following: | ||
CISC 497 | Social, Ethical and Legal Issues in Computing | 3.0 |
F. Complete 3.0 units from the following: | 3.0 | |
CISC 499 | Advanced Undergraduate Project | |
CISC 500 | Undergraduate Thesis | |
Mathematics and Statistics: | ||
G. Complete 6.0 units from the following: | 6.0 | |
MATH 110 | Linear Algebra | |
or | ||
MATH 111 & CISC 102 |
Linear Algebra and Discrete Mathematics for Computing l |
|
H. Complete 6.0 from the following: | 6.0 | |
MATH 120 | Differential and Integral Calculus | |
MATH 121 | Differential and Integral Calculus | |
MATH 123 & MATH 124 |
Differential and Integral Calculus I and Differential and Integral Calculus II |
|
I. Complete 6.0 units from the following: | 6.0 | |
MATH 210 | Rings and Fields | |
MATH 211 | Algebraic Methods | |
MATH 310 | Group Theory | |
MATH 311 | Elementary Number Theory | |
MATH 413 | Introduction to Algebraic Geometry | |
MATH 414 | Introduction to Galois Theory | |
J. Complete 3.0 units from the following: | 3.0 | |
MATH 221 | Vector Calculus | |
MATH 280 | Advanced Calculus | |
K. Complete the following: | ||
STAT 269 | Statistics and Probability II | 3.0 |
STAT 361 | Applied Methods in Statistics I | 3.0 |
STAT 463 | Fundamentals of Statistical Inference | 3.0 |
L. Complete 3.0 units from following: | 3.0 | |
STAT 252 | Introductory Applied Probability | |
STAT 268 | Statistics and Probability I | |
STAT 351 | Probability I |
2. Option
Code | Title | Units |
---|---|---|
A. Complete 12.0 units from the following: | 12.0 | |
COMA_Options |
3. Elective Courses: 36.0 Units
Courses in Other Departments Usable as COMA Courses (COMA_Options)
Code | Title | Units |
---|---|---|
BIOM 300 | Modeling Techniques in Biology | 3.0 |
CISC 271 | Linear Data Analysis | 3.0 |
CISC 330 | Computer-Integrated Surgery | 3.0 |
CISC 371 | Nonlinear Data Analysis | 3.0 |
CISC 372 | Advanced Data Analytics | 3.0 |
CISC 422 | Formal Methods in Software Engineering | 3.0 |
CISC 455 | Evolutionary Optimization and Learning | 3.0 |
CISC 457 | Image Processing and Computer | 3.0 |
CISC 462 | Computability and Complexity | 3.0 |
CISC 465 | Semantics of Programming Languages | 3.0 |
CISC 466 | Algorithms II | 3.0 |
CISC 467 | Fuzzy Logic | 3.0 |
CISC 472 | Medical Informatics | 3.0 |
CISC 473 | Deep Learning | 3.0 |
CISC 500 | Undergraduate Thesis | 6.0 |
MATH 337 | Stochastic Models in Operations Research | 3.0 |
MATH 339 | Evolutionary Game Theory | 3.0 |
MATH 401 | Graph Theory | 3.0 |
MATH 402 | Enumerative Combinatorics | 3.0 |
MATH 406 | Introduction to Coding Theory | 3.0 |
MATH 413 | Introduction to Algebraic Geometry | 3.0 |
MATH 414 | Introduction to Galois Theory | 3.0 |
MATH 418 | Number Theory and Cryptography | 3.0 |
MATH 474 | Information Theory | 3.0 |
MATH 477 | Data Compression and Source Coding | 3.0 |
STAT 361 | Applied Methods in Statistics I | 3.0 |
STAT 456 | Bayesian Analysis | 3.0 |
STAT 457 | Statistical Learning II | 3.0 |
STAT 462 | Statistical Learning I | 3.0 |
STAT 463 | Fundamentals of Statistical Inference | 3.0 |
STAT 464 | Discrete Time Series Analysis | 3.0 |
STAT 471 | Sampling and Experimental Design | 3.0 |
STAT 473 | Generalized Linear Models | 3.0 |
STAT 486 | Survival Analysis | 3.0 |