Background Courses:

Linear Algebra

EAS 205: Applications of Scientific Computation
MATH 312: Linear Algebra
AMCS 602: Numerical Linear Algebra


ESE 301: Engineering Probability

Introductory Courses:

CIS 419/519: Applied Machine Learning
CIS 520: Machine Learning

Advanced Courses:

CIS 620: Advanced Topics in Machine Learning (Fall 2018)
CIS 625: Introduction to Computational Learning Theory
CIS 680: Advanced Topics in Machine Perception (Fall 2018)
CIS 700/004: Topics in Machine Learning and Econometrics (Spring 2017)
CIS 700/007: Deep Learning Methods for Automated Discourse (Spring 2017)
CIS 700/002: Mathematical Foundations of Adaptive Data Analysis (Fall 2017)
CIS 700/006: Advanced Machine Learning (Fall 2017)

STAT 928: Statistical Learning Theory
STAT 991: Topics in Deep Learning (Fall 2018)
STAT 991: Optimization Methods in Machine Learning (Spring 2019)

Other Related Courses:

CIS 530: Computational Linguistics
CIS 535: Introduction to Bioinformatics
CIS 536: Introduction to Computational Biology and Biological Modeling
CIS 537: Biomedical Image Analysis
CIS 630: Advanced Topics in Natural Language Processing
CIS 677: Randomized Algorithms
CIS 700/003: Big Data Analytics (Spring 2017)

ESE 504: Introduction to Optimization Theory
ESE 530: Elements of Probability Theory and Random Processes
ESE 545: Data Mining
ESE 605: Modern Convex Optimization
ESE 674: Information Theory
ESE 680: Combinatorial Optimization

MATH 580: Combinatorial Analysis and Graph Theory

STAT 512: Mathematical Statistics
STAT 542: Bayesian Methods and Computation

Course Catalogs

Undergrad/Grad Undergrad/Grad Undergrad | Grad UndergradGrad