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Graduate Programs
MS in Artificial Intelligence course requirements and sample curriculum
The Master's in Artificial Intelligence Engineering program is intended for students with sufficient computing background as a foundation for the more advanced skills needed to adapt, implement, extend, optimize and troubleshoot AI systems, both in terms of the algorithms on which those systems rely and of the computing infrastructure needed to run them. The master's degree requires a minimum of 30 credit hours, with 18 credit hours of core requirements and 12 credit hours of electives. Students must maintain an average grade of B- (GPA 2.7) for all 30 credit hours.
Students typically will follow a course progression like this, completing all required core courses in the first three semesters.
First Semester
- Foundations of AI Core Course (3 credit hours)
- Machine Learning Foundations Core Course (3 credit hours)
- Natural Language Processing Core Course (3 credit hours)
Second Semester
- Computer Vision Core Course (3 credit hours)
- Computational Methods Core Course (3 credit hours)
- AI Depth Elective (3 credit hours)
Third Semester
- Human-Centered Computing Core Course (3 credit hours)
- AI Depth Elective (3 credit hours)
- AI General Elective (3 credit hours)
Fourth Semester
- AI General Elective (3 credit hours)
Bulletin information about the MS in Artificial Intelligence Engineering
The program will help you understand not only how to build powerful AI systems, but also how to apply them thoughtfully to solve complex, real-world problems, while drawing from a range of application domains. McKelvey's program distinguishes itself through its faculty, interdisciplinary reach and connections to consequential research and applications.
Artificial intelligence is reshaping industries and professions, resulting in a booming demand for skilled engineers who can do more than just use AI tools. Employers need experts who can design, evaluate and deploy reliable AI systems for complex, real-world applications. WashU’s McKelvey School of Engineering is uniquely positioned to prepare students for that work. We bring together faculty who are leaders in their field, rigorous technical training in a top research university and a supportive environment dedicated to helping students thrive.