Curriculum: Electives

In addition to meeting the four core area requirements, each student is required to complete five elective courses. These courses are required for getting a complete breadth in ML. These courses must be chosen from at least two of the five subject areas listed below. In addition, students can use up to six special problems research hours to satisfy this requirement. 

After core requirements are satisfied, all courses listed in the core not already taken can be used (as appropriately classified) electives. 

Course offerings are subject to change. 

Statistics and Applied Probability: To build breadth and depth in the areas of statistics and probability as applied to ML

  • AE 6505, Kalman Filtering

  • AE 8803, Gaussian Processes

  • BMED 6700, Biostatistics (rarely offered)

  • ECE 6558, Stochastic Systems

  • ECE 6601, Random Processes

  • ECE 6605, Information Theory

  • ISYE 6402, Time Series Analysis

  • ISYE 6404, Nonparametric Data Analysis

  • ISYE 6413, Design and Analysis of Experiments

  • ISYE 6414, Regression Analysis

  • ISYE 6416, Computational Statistics

  • ISYE 6420, Bayesian Statistics

  • ISYE 6761, Stochastic Processes I

  • ISYE 6762, Stochastic Processes II

  • ISYE 7400, Adv Design-Experiments

  • ISYE 7401, Adv Statistical Modeling

  • ISYE 7405, Multivariate Data Analysis

  • ISYE 8803, Statistical and Probabilistic Methods for Data Science (rarely offered)

  • ISYE 8813, Special Topics in Data Science 

  • MATH 6221, Probability Theory for Scientists and Engineers

  • MATH 6266, Statistical Linear Modeling

  • MATH 6267, Multivariate Statistical Analysis

  • MATH 7244, Stochastic Processes and Stochastic Calculus I

  • MATH 7245, Stochastic Processes and Stochastic Calculus II

 

Advanced Theory: To build a deeper understanding of foundations of ML

  • AE 8803, Optimal Transport Theory and Applications

  • CS 7280, Network Science (rarely offered)

  • CS 7510, Graph Algorithms (rarely offered)

  • CS 7520, Approximation Algorithms (rarely offered)

  • CS 7530, Randomized Algorithms (rarely offered)

  • CS 7535, Markov Chain Monte Carlo Algorithms 

  • CS 7540, Spectral Algorithms (rarely offered)

  • CS 8803 CA, Continuous Algorithms (rarely offered)

  • ECE 6283, Harmonic Analysis and Signal Processing (rarely offered)

  • ECE 6555, Optimal Estimation

  • ISYE 7682, Convexity (rarely offered)

  • MATH 6112, Advanced Linear Algebra

  • MATH 6262, Advanced Statisical Inference 

  • MATH 6241, Probability I

  • MATH 6263, Testing Statistical Hypotheses 

  • MATH 6580, Introduction to Hilbert Space

  • MATH 7338, Functional Analysis

  • MATH 7586, Tensor Analysis (rarely offered)

 

Applications: To develop a breadth and depth in variety of applications domains impacted by/with ML

  • AE 6373, Advanced Design Methods

  • AE 8803, Machine Learning for Control Systems (rarely offered)

  • AE 8803, Nonlinear Stochastic Optimal Control

  • BMED 6780, Medical Image Processing

  • BMED/ECE 6790, Information Processing Models in Neural Systems

  • BMED 7610, Quantitative Neuroscience

  • BMED 8813BHI, Biomedical and Health Informatics

  • BMED 8813MHI, mHealth Informatics

  • BMED 8813MLB, Machine Learning in Biomedicine (rarely offered)

  • BMED 8823ALG, OMICS Data and Bioinformatics Algorithms (rarely offered)

  • CHBE 6745, Data Analytics for Chemical Engineers

  • CHBE 6746, Data-Driven Process Engineering

  • CS 6440, Introduction to Health Informatics

  • CS 6465, Computational Journalism (rarely offered)

  • CS 6471, Computational Social Science

  • CS 6474, Social Computing

  • CS 6475, Computational Photography (rarely offered)

  • CS 6476, Computer Vision

  • CS 6601, Artificial Intelligence

  • CS 7450, Information Visualization

  • CS 7476, Advanced Computer Vision

  • CS 7630, Autonomous Robots (rarely offered)

  • CS 7632, Game AI

  • CS 7636, Computational Perception (rarely offered)

  • CS 7643, Deep Learning

  • CS 7646, Machine Learning for Trading (rarely offered)

  • CS 7647, Machine Learning with Limited Supervision

  • CS 7650, Natural Language Processing

  • CSE 6141, Massive Graph Analysis (rarely offered)

  • CSE 6240, Web Search and Text Mining

  • CSE 6242, Data and Visual Analytics

  • CSE 6301, Algorithms in Bioinformatics and Computational Biology (rarely offered)

  • ECE 4580, Computational Computer Vision (rarely offered)

  • ECE 6255, Digital Processing of Speech Signals

  • ECE 6258, Digital Image Processing

  • ECE 6260, Data Compression and Modeling

  • ECE 6273, Methods of Pattern Recognition with Application to Voice

  • ECE 6550, Linear Systems and Controls

  • ECE 8813, Network Security (rarely offered)

  • ISYE 6421, Biostatistics (rarely offered)

  • ISYE 6810, Systems Monitoring and Prognosis

  • ISYE 7201, Production Systems

  • ISYE 7204 Info Prod & Ser Sys

  • ISYE 7203, Logistics Systems

  • ISYE 8813, Supply Chain Inventory Theory

  • HS 6000, Healthcare Delivery

  • MATH 6759, Stochastic Processes in Finance

  • MATH 6783, Financial Data Analysis (rarely offered)

 

Computing and Optimization: To provide more breadth and foundation in areas of math, optimization, and computation for ML

  • AE 6513, Mathematical Planning and Decision-Making for Autonomy 

  • AE 8803, Optimization-Based Learning Control and Games

  • CS 6515, Introduction to Graduate Algorithms

  • CS 6550, Design and Analysis of Algorithms

  • CSE 6140, Computational Science and Engineering Algorithms

  • CSE 6643, Numerical Linear Algebra

  • CSE 6644, Iterative Methods for Systems of Equations

  • CSE 6710, Numerical Methods I (not offered)

  • CSE 6711, Numerical Methods II (rarely offered)

  • ECE 6553, Optimal Control and Optimization 

  • ISYE 6644, Simulation

  • ISYE 6645, Monte Carlo Methods

  • ISYE 6662, Discrete Optimization

  • ISYE 6664, Stochastic Optimization

  • ISYE 6679, Computational methods for optimization

  • ISYE 7686, Advanced Combinatorial Optimization

  • ISYE 7687, Advanced Integer Programming (rarely offered)

 

Platforms: To provide breadth and depth in computing platforms that support ML and Computation

  • CS 6421, Temporal, Spatial, and Active Databases (rarely offered)

  • CS 6430, Parallel and Distributed Databases (rarely offered)

  • CS 6290, High-Performance Computer Architecture

  • CSE 6220, High Performance Computing

  • CSE 6230, High Performance Parallel Computing