Data Analytics is a new way of understanding complex systems by building computational models that are consistent with the observed data about those systems. It's used in applications such as understanding customers, making effective investment decisions, recommending shows on platforms like Netflix, detecting cyberintrusions or financial fraud, and much more.
Program Requirements
The following are the requirements for the Data Analytics option within the Computing Major. 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 

A. Complete the following:  
CISC 121  Introduction to Computing Science I  3.0 
CISC 124  Introduction to Computing Science II  3.0 
B. Complete 3.0 units from the following:  3.0  
STAT 263  Introduction to Statistics  
STAT 268  Statistics and Probability I  
STAT 351  Probability I  
STAT_Options  
C. 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 
D. Complete 3.0 units from the following:  3.0  
CISC 322  Software Architecture  
CISC 326  Game Architecture  
E. Complete the following:  
CISC 324  Operating Systems  3.0 
CISC 360  Programming Paradigms  3.0 
CISC 365  Algorithms I  3.0 
F. Complete the following:  
CISC 497  Social, Ethical and Legal Issues in Computing  3.0 
G. Complete 3.0 units from the following:  3.0  
CISC 496  Game Development Project  
CISC 499  Advanced Undergraduate Project  
CISC 500  Undergraduate Thesis 
2. Option  Data Analytics
Code  Title  Units 

A. a) Complete the following:  
CISC 271  Linear Data Analysis  3.00 
CISC 371  Nonlinear Data Analysis  3.00 
CISC 372  Advanced Data Analytics  3.00 
CISC 451  Topics in Data Analytics  3.00 
CISC 452  Neural and Genetic Computing  3.00 
B. Complete 3.0 units from the following:  3.0  
CISC, COCA, COGS, or SOFT at the 200level or above 
3. Supporting
Code  Title  Units 

A. Complete 6.0 units from the following:  6.0  
CISC 102 & MATH 111 
Discrete Mathematics for Computing l and Linear Algebra 

CISC 102 & MATH 112 
Discrete Mathematics for Computing l and Introduction to Linear Algebra 

MATH 110  Linear Algebra  
B. Complete 6.0 units from the following:  6.0  
MATH 120  Differential and Integral Calculus  
MATH 121  Differential and Integral Calculus  
MATH 123  Differential and Integral Calculus I  
MATH 124  Differential and Integral Calculus II 
Elective Courses: 48.00 Units
Students should consider focussing their electives on a Minor in another topic.
Statistics Course List (STAT_Options)
Code  Title  Units 

BIOL 243  Introduction to Statistics  3.0 
CHEE 209  Analysis Of Process Data  3.5 
COMM 162  Managerial Statistics  3.0 
ECON 250  Introduction to Statistics  3.0 
GPHY 247  Introduction to Statistics  3.0 
KNPE 251  Introduction to Statistics  3.0 
NURS 323  Introduction to Statistics  3.0 
POLS 385  Introduction to Statistics  3.0 
PSYC 202  Statistics in Psychology  3.0 
SOCY 211  Introduction to Statistics  3.0 
STAM 200  Introduction to Statistics  3.0 
STAT 263  Introduction to Statistics  3.0 
STAT 367  Engineering Data Analysis  4.0 
CISC Substitutions Course List (CISC_Subs)
Code  Title  Units 

COMM 365  Advanced Business Decision Modeling  
ELEC 470  Computer System Architecture  
ELEC 474  Machine Vision  
MATH 272  Applications of Numerical Methods  
MATH 337  Stochastic Models in Operations Research  
MATH 401  Graph Theory  
MATH 402  Enumerative Combinatorics  
MATH 434  Optimization Theory and Applications  
MATH 474  Information Theory 