MSSWE Machine Learning and Data Science Plan of Study

This sample plan of study is a guideline. You can create a plan of study that meets your specific needs, as long as it complies with the MSSWE degree requirements. 

Degree Requirements

Total credits needed: 30

• Two core courses:
  • Select one:
    • ECE 60800, Computational Models and Methods (3 credits)
    • CS 58000, Algorithm Design, Analysis, and Implementation (3 credits)
  • ECE 59500, Advanced Software Engineering (3 credits)
• One math course (3 credits)
  • ECE graduate student math course options
• A total of 18 credit hours of ECE and CS coursework, includes core courses

Recommended courses:

Course	Title	Offerings	Term(s) Offered	Credit Hours
ECE 50024	Machine Learning	On-campus and online	Spring	3
ECE 50863	Introduction to Data Mining	On-campus and online	Fall	3
ECE 56200	Introduction to Data Management	On-campus only	Fall - odd years	3
ECE 57000	Artificial Intelligence	On-campus and online	Fall, Spring	3
ECE 59500	Deep Learning for Computer Vision	On-campus only	Fall	3
ECE 59500	Introduction to Deep Learning	On-campus and online	Fall	3
ECE 59500	Natural Language Processing	On-campus only	Spring	3
ECE 59500	Reinforcement Learning	On-campus and online	Fall	3
ECE 60146	Deep Learning	On-campus only	Spring	3
ECE 62900	Introduction to Neural Networks	On-campus and online	Fall	3
ECE 66100	Computer Vision	On-campus only	Fall - even years	3
ECE 69500	Inference and Learning in Generative Models	On-campus only	Spring	3
ECE 69500	Machine Learning for Bioinformatics and Healthcare	On-campus and online	Spring	3
ECE 69500	Optimization for Deep Learning	On-campus and online	Fall	3
ECE 69500	Big Data for Reliabilty and Security	On-campus and online	Fall	1
CS 57300	Data Mining (Prerequisite: STAT 51600, Basic Probability and Applications)	On-campus and online		3

Recommended math courses:

• MA 51100: Linear Algebra
• STAT 51600: Basic Probability and Applications