Master of Science in Machine Learning


This is a new degree offering beginning in the fall of 2023, coinciding with MSOE’s transition to a semester system. It consists of 8, 4-credit courses.

All courses will be offered online (fully virtual or in classroom with technology enabling remote participation). Nearly all courses will be synchronous. The 4 classes that are part of graduate certificates (see track below) will be offered in the evening.

The program and course information for the 2023-2024 graduate catalog (plus the undergraduate catalog) were approved early in 2022 and will be published by MSOE on January 6, 2023.

Students who were in the 2021-22 cohort of our applied ML graduate certificate, upon which the core classes in the MS ML are based, were generally working full-time and said that it was better for them to take 1 course at a time instead of 2. So, for the master’s degree, that would translate to 3+ years depending on how many summer classes are taken. The program could be done in 2 years or a bit less if someone took 2 courses at a time.

We expect that many of the students in the program will have tuition support from their employers. Depending on the company, taking one course at a time might also be the best path from a financial perspective if the employer has annual limits on tuition support.

More information will be posted soon. Please contact MS ML program director Dr. Durant with any questions.

University Website: MSOE M.S. in Machine Learning

Admissions Pathways

Dual Enrollment with Bachelor’s Degree

Direct Admit to MS ML requirements (also apply to Graduate Certificate in Applied Machine Learning)

Model 2-year Track

MSOE CS students and graduates replace CSC5610 and MTH5810 with approved electives.

Course Details

Course Type Title Structure Offered Prerequisites
CSC5120 Background Software Development for Machine Learning 4-0-4 summer beginning ‘23 CSC1110 | CSC1310 | consent
CSC5201 Required Microservices and Cloud Computing 4-0-4 spring SWE2710 | (CSC3320 & CSC3210) | CPE2600 | consent | …
CSC5241 Elective GPU Programming      
CSC5601 Elective Theory of Machine Learning 4-0-4 fall & spring (MTH2130 & MTH2340 & CSC2610) | consent
CSC5610 Required AI Tools and Paradigms 4-0-4 fall & spring (MTH2130 | MTH2340 | MTH5810) & (CSC1120 | equivalent) | consent
CSC5611 Elective Deep Learning 4-0-4 spring CSC4601 | CSC5601 | CSC6621 | consent
CSC5651 Elective Deep Learning in Signal Processing 4-0-4 fall, 2023 then again in 2025-‘26  
CSC5980(1) Elective Topics in Computer Science (with Laboratory) varies    
CSC6605 Required Machine Learning Production Systems 4-0-4 fall & summer CSC6621 | CSC4601 | consent
CSC6621 Required Applied Machine Learning 4-0-4 spring & summer (CSC5610 | CSC2621) & (MTH2130 | MTH2340 | MTH5810) | consent | CS2300
CSC6980 Elective Topics in Computer Science varies    
CSC6999 Elective Computer Science Independent Study varies    
CSC7901 Required Machine Learning Capstone 4-0-4 all terms ≤ 1 year to completion
MTH5810 Background Mathematical Methods for Machine Learning 4-0-4 fall beginning ‘24 Enrolled in MS ML
PHL6001 Required AI Ethics and Governance 4-0-4 likely summers beginning ‘24 None

Notes on Terms Offered