Artificial Intelligence Graduate Major (MENG, MS, PhD)
Artificial Intelligence (AI) is the study of intelligent artifacts and the principles behind their design, construction, and analysis. Oregon State has a long history of excellence in AI since the early days of computer science. The field traces its origin to many disciplines, including philosophy, psychology, mathematics, and engineering. Today, AI is making contributions to all areas of science, engineering and humanities. To encompass this diversity, the AI program offers a direct pathway for well-motivated and computationally oriented students from any discipline to enter the field of AI and start making contributions.
In addition to offering many courses and supporting research in the core topics of AI such as machine learning, knowledge representation, reasoning under uncertainty, sequential decision making, natural language processing, and computer vision and robotics, the program allows great flexibility for students to choose relevant courses from a wide range of other disciplines. It is expected that the students in this program will:
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Get a rigorous education in AI and its social impact
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Conduct state of the art research in AI
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Develop innovative new techniques and applications of AI
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Publish research in top tier venues
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Work closely with experts in AI and other disciplines where appropriate
The AI program at Oregon State University offers the following degree types:
PhD degree is aimed at students who will be taking research and teaching positions in academia, industry and government, and leading AI companies.
MS degree with a thesis option qualifies students for research and development positions in the AI industry.
MS degree with a project option qualifies students to get software development jobs in industry.
MEng degree is for industry-oriented students with a focus on coursework and a flexible project experience.
Major Code: 3075
Master of Engineering (MEng)
| Code | Title | Credits |
|---|---|---|
| Algorithms course | 4 | |
| AI 530 | 2 | |
| Ethical and social issues course | 3 | |
| Core AI courses 1 | minimum 12 | |
| Non-core courses approved by committee + | minimum 12 | |
| Capstone | 3-6 | |
| Total Credits | 45 | |
Master of Science (MS)
| Code | Title | Credits |
|---|---|---|
| MS thesis or project requirement | 6-9 | |
Thesis (9 research credits) | ||
Project (6 project credits) | ||
| Algorithms course | 4 | |
| AI 530 | 2 | |
| Ethical and social issues course | 3 | |
| Core AI courses 1 | minimum 12 | |
| Non-core courses approved by committee + | minimum 12 | |
| Total Credits | 45 | |
Doctor of Philosophy (PhD)
| Code | Title | Credits |
|---|---|---|
| Dissertation | minimum 36 | |
| Algorithms course | 4 | |
| Ethical and social issues course | 3 | |
| AI 530 | 2 | |
| Core AI courses 1 | minimum 16 | |
| Non-core courses approved by committee + | minimum 16 | |
| Total Credits | 108 | |
Core AI Courses1
| Code | Title | Credits |
|---|---|---|
| AI 531 | ARTIFICIAL INTELLIGENCE | 4 |
| AI 533 | INTELLIGENT AGENTS AND DECISION MAKING | 4 |
| AI 534 | MACHINE LEARNING | 4 |
| AI 535 | DEEP LEARNING | 4 |
| AI 536 | PROBABILISTIC GRAPHICAL MODELS | 4 |
| AI 537 | COMPUTER VISION I | 3 |
| AI 538 | (pending approval) | |
| AI 637 | COMPUTER VISION II | 4 |
| PHL 546 | (satisfies ethics requirement) | 3 |
| ROB 534 | SEQUENTIAL DECISION MAKING IN ROBOTICS | 4 |
| ROB 538 | MULTIAGENT SYSTEMS | 4 |
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Non-core courses must be approved by the program committee based on the student's background and educational and research needs
Major Code: 3075