Artificial Intelligence (AI) has been a core strength of the School of Computing for many years. Here, we highlight the various ways AI is playing a role (and can be found) in both the education provided by the School of Computing, as well as the research conducted by its faculty.
Research
The School of Computing proudly houses over a dozen faculty members that focus on a range of AI fields from machine/deep learning to evolutionary computing to AI in medicine/health. You can find a list of the faculty members and related labs here.
Education
There are two dedicated programs to AI offered by the School; one at the Undergraduate level and one for Graduate students.
For Undergraduates, the sub-plan in Artificial Intelligence offers a rich set of courses to learn about various forms of AI through your entire degree.
For Graduate students, the Vector approved Field of Study in AI program is dedicated to students wishing to take AI-specific courses and complete a related dissertation on the topic.
Many of our courses incorporate Generative AI in both the delivery and assessments of the material.
The list of AI-related courses is growing constantly, and we currently offer a wide range of topics that primarily focus on either the theory behind, or applications of, Artificial Intelligence. These are the courses that we have offered recently (and plan to offer again):
Undergraduate Courses
| Course Code | Course Title |
|---|---|
| ARIN 100 | Fundamentals of Artificial Intelligence |
| ARIN 101 | Artificial Intelligence in Society |
| ARIN 201 | Ethics and Fairness in Artificial Intelligence |
| ARIN 210 | Applications of Artificial Intelligence |
| COGS 100 | Introduction to Cognitive Science |
| COGS 201 | Cognition and Computation |
| CISC 352 | Artificial Intelligence |
| CISC 271 | Linear Methods for Artificial Intelligence |
| CISC 330 | Computer-Integrated Surgery |
| CISC 351 | Advanced Data Analytics |
| CISC 371 | Numerical Optimization for Artificial Intelligence |
| CISC 372 | Advanced Data Analytics |
| CISC 451 | Topics in Data Analytics |
| CISC 452 | Neural and Genetic Computing |
| CISC 455 | Evolutionary Optimization and Learning |
| CISC 471 | Computational Biology |
| CISC 472 | Medical Informatics |
| CISC 473 | Deep Learning |
| CISC 474 | Reinforcement Learning |
Graduate Courses
| Course Code | Course Title |
|---|---|
| CISC 813 | Automated Planning |
| CISC 843 | Mining Software Repositories |
| CISC 851 | Evolutionary Computing |
| CISC 855 | Nonlinear Optimization |
| CISC 856 | Reinforcement Learning |
| CISC 867 | Deep Learning |
| CISC 873 | Data Mining |
| CISC 874 | Neural and Cognitive Computing |
| CISC 881 | Medical Imaging and Machine Learning |
There are several initiatives underway with the sub-committee on AI in Education at the School of Computing, and we will update this space as they become a reality.
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