Pre Approved M.S. Electives

Pre Approved Electives (please note courses are not offered every quarter or every year)

Econ 111A,B,C:  Intermediate Accounting (with permission of instructor)
Econ 124:  Machine Learning for Economists
Econ 188:  Management in the Global Economy
Econ 211C:  Ph.D. Time Series (with permission of instructor)
Econ 231:  International Financial Markets
Econ 234:  Financial Institutions and Markets
Econ 235:  Corporate Finance
Econ 238:  Market Design: Theory and Pragmatics
Econ 259B:  Public Policy Analysis

Applied Mathematics
AM 216:  Stochastic Differential Equations

Computer Science & Engineering
CSE 20:  Introduction to Programming in Python*
CSE 101:  Algorithms and Abstract Data Types
CSE 102:  Introduction to Analysis of Algorithms
CSE 111:  Advanced Programming (with permission of instructor)
CSE 142:  Machine Learning (with permission of instructor)
CSE 182:  Introduction to Database Management Systems
CSE 201:  Analysis of Algorithms (with permission of instructor)
CSE 202:  Combinatorial Algorithms (with permission of instructor)
CSE 243:  Data Mining (with permission of instructor)
CSE 270B:  Management of Technology II (with permission of instructor)
CSE 271:  E-Business Technology and Strategy (with permission of instructor)
CSE 272:  Information Retrieval (with permission of instructor)
CSE 277:  Random Process Models in Engineering (with permission of instructor)

*As it is a lower-division course, CSE 20, does not count toward the 35 credits required by the university to obtain a masters degree. However, since it broadens the skill-set of students in the program, we allow for it as a masters elective to satisfy department requirements. Before enrolling in this course, students should take care to ensure that they will have 35 eligible credits for graduation.

Environmental Studies
ENVS 140:  National Environmental Policy

STAT 206:  Applied Bayesian Statistic
STAT 206B:  Intermediate Bayesian Inference
STAT 207:  Intermediate Bayesian Statistical Modeling
STAT 208:  Linear Statistical Models
STAT 226:  Spatial Statistics