Artificial Intelligence, MSE
The online Master of Science in Engineering in Artificial Intelligence (MSE-AI Online) graduate-level program enables students with a computer science background to keep up and ahead of industry demand by exploring algorithms for knowledge-based agents, large language models, natural language processing, and deep learning. MSE-AI Online allows students from around the world to benefit from the research and teaching expertise of Penn’s world-renowned experts. While studying from the comfort of home, students take part in assignments that engage real-world tools and environments.
For more information: https://online.seas.upenn.edu/degrees/mse-ai-online
The degree and major requirements displayed are intended as a guide for students entering in the Fall of 2026 and later. Students should consult with their academic program regarding final certifications and requirements for graduation.
Curriculum
| Code | Title | Course Units |
|---|---|---|
| Requirements | ||
| Core Courses | 7 | |
| Artificial Intelligence | ||
| Natural Language Processing | ||
| Internet and Web Systems 1 | ||
or CIS 5690 | GPU Computing for Machine Learning Systems | |
| Machine Learning for Data Science | ||
| Statistics for Data Science | ||
| Principles of Deep Learning | ||
| Technology Ethics and the Legal Landscape | ||
| Technical Electives | 2 | |
| Select 2 CU from the following: | ||
| Algorithms for Big Data | ||
| Networked Systems | ||
| Computer Vision & Computational Photography | ||
| Artificial Intelligence Capstone | ||
Or one of the Core Courses 2 | ||
| Free Elective | 1 | |
Any online EAS/CIS/ESE/ENGR course or 3 | ||
| Digital Health 4 | ||
| Total Course Units | 10 | |
- 1
Either CIS 5550 Internet and Web Systems or CIS 5690 GPU Computing for Machine Learning Systems, but not both, must be taken as one of the 7 core courses.
- 2
If you take eight core courses, one can be used to fulfill a technical elective requirement.
- 3
See Penn Engineering Online course catalog.
- 4
HCIN 6022 should only be taken as an elective if students plan to apply for the Graduate Certificate in Health Care and Technology from the Perelman School of Medicine. All SEAS students entering the Graduate Certificate in Health Care and Technology must take this course as part of their degree studies. SEAS students taking this course for credit in an engineering degree must complete a final project focused on an area of computer science.
| First Year | ||
|---|---|---|
| Fall | Course Units | |
| CIS 5210 | Artificial Intelligence | 1 |
| Course Units | 1.00 | |
| Spring | ||
| CIS 5300 | Natural Language Processing | 1 |
| Course Units | 1.00 | |
| Summer | ||
| ESE 5410 | Machine Learning for Data Science | 1 |
| Course Units | 1.00 | |
| Second Year | ||
| Fall | ||
| CIS 5550 or CIS 5690 | Internet and Web Systems or GPU Computing for Machine Learning Systems | 1 |
| Course Units | 1.00 | |
| Spring | ||
| ESE 5420 | Statistics for Data Science | 1 |
| Course Units | 1.00 | |
| Summer | ||
| 1 CU Technical Elective | 1 | |
| Course Units | 1.00 | |
| Third Year | ||
| Fall | ||
| ESE 5460 | Principles of Deep Learning | 1 |
| Course Units | 1.00 | |
| Spring | ||
| EAS 5240 | Technology Ethics and the Legal Landscape | 1 |
| Course Units | 1.00 | |
| Summer | ||
| 1 CU Free Elective | 1 | |
| Course Units | 1.00 | |
| Fourth Year | ||
| Fall | ||
| 1 CU Technical Electives | 1 | |
| Course Units | 1.00 | |
| Total Course Units | 10.00 | |