Machine Learning and Data Science Plan of Study
Master's in Software EngineeringThis 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 Master of Science in Software Engineering degree requirements.
Degree Requirements
This degree requires 30 credit hours total with at least 18 hours of electrical and computer engineering and computer science course work, including 2 ECE core courses, and 3 credit hours of graduate math coursework.
Chose one from the following:
- ECE 60800: Computational Models and Methods (3 credits)
- Modality: On-campus, online
- Location: West Lafayette, Indianapolis
- CS 58000: Algorithm Design, Analysis, and Implementation (3 credits)
- Modality: On-campus
- Location: West Lafayette
AND
- ECE 50874: Advanced Software Engineering (3 credits)
- Modality: On-campus, online
- Location: West Lafayette
Students must take 3 credit hours of graduate mathematics. Please see the list of approved courses here.
The following are recommend math courses for a Machine Learning and Data Science Plan of Study:
- MA 51100: Linear Algebra
- STAT 51600: Probability and Applications
Students can earn the Machine Learning and Data Science concentration by completing 9 credit hours from this list; additional relevant coursework may be approved by the student’s plan of study advisor.
- ECE 50024: Machine Learning (3 credit hours)
- Modality: On-campus, online
- Term Offered: Spring
- ECE 50863: Introduction to Data Mining (3 credit hours)
- Modality: On-campus, online
- Term Offered: Fall
- ECE 56200: Introduction to Data Management (3 credit hours)
- Modality: On-campus
- Term Offered: Fall, odd years
- ECE 57000: Artificial Intelligence (3 credit hours)
- Modality: On-campus, online
- Term Offered: Fall, Spring
- ECE 59500: Deep Learning for Computer Vision (3 credit hours)
- Modality: On-campus
- Term Offered: Fall
- ECE 59500: Introduction to Deep Learning (3 credit hours)
- Modality: On-campus, online
- Term Offered: Fall
- ECE 59500: Natural Language Processing (3 credit hours)
- Modality: On-campus
- Term Offered: Spring
- ECE 59500: Reinforcement Learning (3 credit hours)
- Modality: On-campus, online
- Term Offered: Fall
- ECE 60146: Deep Learning (3 credit hours)
- Modality: On-campus
- Term Offered: Spring
- ECE 62900: Introduction to Neural Networks (3 credit hours)
- Modality: On-campus, online
- Term Offered: Fall
- ECE 66100: Computer Vision (3 credit hours)
- Modality: On-campus
- Term Offered: Fall, even years
- ECE 60131: Inference and Learning in Generative Models (3 credit hours)
- Modality: On-campus
- Term Offered: Spring
- ECE 69500: Machine Learning for Bioinformatics and Healthcare (3 credit hours)
- Modality: On-campus, online
- Term Offered: Spring
- ECE 69500: Optimization for Deep Learning (3 credit hours)
- Modality: On-campus, online
- Term Offered: Fall
- ECE 69500: Big Data for Reliability and Security (1 credit hour)
- Modality: On-campus, online
- Term Offered: Fall
- CS 57300: Data Mining (3 credit hours)
- Prerequisite: STAT 51600: Basic Probability and Applications
- Modality: On-campus, online