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 uptodate 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 halfyear/oneterm course is worth 3.0 units, while a fullyear/twoterm 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  ComputerIntegrated 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 