University at Buffalo School of Engineering and Applied Sciences 33 courses 30 total credits
This Engineering Sciences MS with a course focus on Artificial Intelligence (AI) is a multidisciplinary program designed to train students in the areas of machine learning, programming languages, deep learning algorithms, and advanced artificial neural networks that use predictive analytics to solve real-world problems. Students in this program take foundational courses in AI and can choose from elective concentrations like data analytics, computational linguistics and information retrieval, machine learning and computer vision, knowledge representation, and robotics.
| Total Credits | 30 credits |
Required Core
| Code | Course Title | Credits |
|---|---|---|
| CSE 531 | Algorithms Anal & Dsgn 1 | 3 |
| CSE 546 | Reinforcement Learning | 3 |
| CSE 555 | Intro Pattern Recognition | 3 |
| CSE 574 | Intro Machine Learning | 3 |
| CSE 587 | Data Intensive Computing | 3 |
| EAS 501 | Introduction to Numerical Mathematics for Computing and Data Science | 3 |
| CSE 573 or CSE 635 | Comp Vision & Image Proc or NLP and Text Mining | 3 |
| Total Required Core | 24 credits | |
Electives
Number of elective credits may vary depending on choice of culminating experience. Be sure to complete enough elective credit to reach 30 minimum total credit hours. *Max of 3 MGS credits.
Culminating Experience:Exam or Project
| Code | Course Title | Credits |
|---|---|---|
| EAS 563 | Artificial Intelligence Capstone | 1-3 |
| Total Culminating Experience:Exam or Project | 0-3 credits | |
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