Engineering Artificial Intelligence - MS
The Master of Science in engineering of artificial intelligence (EAI) prepares specialists with comprehensive knowledge in all areas of this new disruptive and revolutionary technology. Gain knowledge in interdisciplinary foundations and practical experience in algorithms, sensors, hardware, control, and applications.
Overview This program consists of a three-semester course sequence which covers the fundamentals of artificial intelligence, probabilistic reasoning, machine learning, deep learning algorithms, sensor electronics, digital systems design and acceleration hardware, control theory and practice, convex optimization, natural language processing, and computer vision and applications in mobile, health, and other domains. Students will obtain a critical computer engineering background, which includes knowledge in sensors, hardware, control, and applications, enabling them to solve real world AI problems. |
Admission requirements
- Bachelor degree or equivalent in Electrical or Computer Engineering or in a related discipline.
- GPA above 3.3
- GRE V150, Q159, WA3 (if required by the graduate school; waived for Fall 2024 for now).
- TOEFL 80, IELTS 6.5
- 3 recommendation letters.
These are the minimum requirements, similar to the CE and EE M.S. programs.
Degree RequirementsThe EAI M.S. program offers both thesis and non-thesis options. A non-thesis option is expected to be finished in three semesters, while a thesis one typically takes four semesters. In general, at least 30 graduate credits with a cumulative and departmental grade point average of 3.0 or better are needed. The details of the program structures and course/credit requirements in different subareas are given below:
Explore Your Future Career Opportunities
AI knowledge and skills are hotly pursued in industry and business these days. Many
students with basic algorithms and software backgrounds in deep learning can secure
high-paying job offers in finance and high-tech industries around the globe.
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