The Master of Science in Engineering and Applied Science is for engineers aspiring to a leadership position in their field or looking to pivot to a new technical focus.
Applicants are expected to have a bachelor’s degree in a STEM field and typically two to five years’ work experience in a technical role. They should be able to articulate a vision for what they want to accomplish after they have graduated with their masters’ degree.
This is a full-time, on-campus, 30-credit program for professionals who are planning their next career move — the program gives engineers the skills necessary to lead at the highest level in a technical organization or to launch a technical start-up.
The Master of Science in Engineering is a full-time STEM designated 30-point program. Students begin in the fall semester and may complete the program in May, August, or December of the following year.
xMS Concentrations
Select nine credits from one concentration.
Advanced Materials and Nanotechnology
Artificial Intelligence and Machine Learning
Course List
| Code |
Title |
Points |
| COMS W4701 | ARTIFICIAL INTELLIGENCE | |
| COMS W4705 | NATURAL LANGUAGE PROCESSING | |
| COMS W4731 | Computer Vision I: First Principles | |
| COMS W4732 | Computer Vision II: Learning | |
| COMS W4773 | Machine Learning Theory | |
| COMS W4774 | Unsupervised Learning | |
| COMS W4775 | Causal Inference | |
| COMS W4776 | Machine Learning for Data Science | |
| COMS W4995 | TOPICS IN COMPUTER SCIENCE (Applied Deep Learning) | |
| COMS W4995 | TOPICS IN COMPUTER SCIENCE (Causal Inference for Data) | |
| COMS W4995 | TOPICS IN COMPUTER SCIENCE ( Deep Learning for Computer Vision ) | |
| COMS W6706 | Advanced Spoken Language Processing | |
| COMS E6998 | TOPICS IN COMPUTER SCIENCE (Reinforcement Learning LLMs) | |
| COMS E6998 | TOPICS IN COMPUTER SCIENCE (Machine Learning Frontiers) | |
| COMS E6998 | TOPICS IN COMPUTER SCIENCE (High Performance Machine Learning) | |
| COMS E6998 | TOPICS IN COMPUTER SCIENCE (Deep Learning for Robot Manipulation) | |
| EAEE E4000 | Machine learning for environmental engineering and science | |
| EAEE E4009 | GIS-RES,ENVIR,INFRASTRUCTR MGT | |
| ECBM E4040 | NEURAL NETWRKS ＆ DEEP LEARNING | |
| EEEL E4220 | Energy System Economics and Optimization | |
| ELEN E6908 | TOPICS IN ELECTRICAL AND COMPUTER ENGINE ( Embedded AI) | |
| IEOR E4523 | Data Analytics and Machine Learning | |
| MECE E4602 | INTRODUCTION TO ROBOTICS | |
| MECS E4603 | APPLIED ROBOTICS: ALGORITHMS＆SOFTWARE | |
| MECE E4611 | ROBOTICS STUDIO | |
| MECE E6612 | Robotics Studio (Advanced) | |
| MECE E6615 | ROBOTIC MANIPULATION | |
| MECE E6616 | ROBOT LEARNING | |
| ORCS E4529 | Reinforcement Learning | |
| ELEN E4720 | Machine Learning for Signals, Information and Data | |
| EECS E4764 | Artificial Intelligence of Things (AIoT) | |
| MEEC E6600 | Mathematics of Machine Learning, Signals, and Control | |
| EECS E6694 | TOPICS DATA-DRIVEN ANAL ＆ COMP (GenAI and Modern Deep Learning ) | |
| EECS E6699 | TOPICS DATA-DRIVEN ANAL ＆ COMP (Mathematics of Deep Learning) | |
| EECS E6720 | BAYESIAN MOD MACHINE LEARNING | |
| ELEN E6820 | SPEECH＆AUDIO PROC＆REC | |
| ELEN E6876 | Sparse and Low-Dimensional Models for High-Dimensional Data | |
| ELEN E6885 | Topics in signal processing (Reinforcement Learning) | |
| EECS E6892 | TOPICS-INFORMATION PROCESSING (Reinforcement Learning in Information Systems) | |
| EECS E6893 | TOPICS-INFORMATION PROCESSING (Big Data Analytics) | |
| EECS E6895 | TOPICS-INFORMATION PROCESSING (Advanced Big Data and Artificial Intelligence) | |
| CSEE W4121 | COMPUTER SYSTEMS FOR DATA SCIENCE | |
| EECS E4750 | Heterogeneous Computing for Signal and Data Processing | |
| EECS E6891 | TOPICS-INFORMATION PROCESSING (Operating, Distributed and Runtime System Optimization through AI/ML Techniques ) | |
| CIEN E4253 | COMP SOLID MECHANICS WITH AI | |
| CIEN E4256 | Applied Machine Learning in Civil Engineering | |
| CHEN E4580 | ARTIFICIAL INTELLIGENCE IN CHEMICAL ENGINEERING | |
| CHEN E4880 | ATOMISTIC SIMULATIONS FOR SCIENCE AND EN | |
| CHEN E4180 | Machine Learning for Biomolecular and Cellular Applications | |
| EAEE E4000 | Machine learning for environmental engineering and science | |
Climate, Energy, and Sustainability
Fintech and Analytics
Medical Device Design
Robotics and Smart Machines
Supply Chain, Retail and Service Systems
Course List
| Code |
Title |
Points |
| IEOR E4108 | SUPPLY CHAIN ANALYTICS | |
| IEOR E4418 | TRANSPORTATION ANALYTICS ＆ LOGISTICS | |
| IEOR E4505 | OPERATION RES IN PUBLIC POLICY | |
| IEOR E4507 | HEALTHCARE OPERATIONS MGT | |
| IEOR E4601 | DYNAMIC PRICING/REVENUE MGMT | |
| EAEE E4200 | Introduction to Sustainable Production of Earth Mineral ＆ Metal Resources | |
| EAEE E4220 | Energy System Economics and Optimization | |
| EAEE E4361 | ECON-EARTH RESOURCE INDUSTRIES | |
