- International Fees
International fees are typically 3.25 times the domestic tuition. Exact cost will be calculated upon completion of registration.
Course Overview
Artificial Intelligence (AI) is the intelligence expected to be demonstrated by machines and computer programs. This course is designed to provide students with expertise in creating and modifying required AI algorithms and techniques. The first part of the course will focus on classic AI solutions (especially decision making) while the second part will cover some of machine learning (ML) related applications of AI (with an emphasis on learning from examples). The course will consider real world problems that need to be solved with applications of AI and the techniques used to build such applications (e.g. using the techniques to create challenging non player characters (NPC) in games development or password strength classification and intrusion detection in network security). More specifically, students will learn about the searching paradigm in designing intelligent agents and will practice implementing search algorithms. Probabilistic reasoning will also be explored to help students learn how to deal with incomplete information and uncertainty. The course will also examine different learning techniques to guide students in creating self-learning models that can improve performance in decision-making over time through practical examples.
Prerequisite(s)
- 60% in COMP 8042
Credits
3.0
- Not offered this term
- This course is not offered this term. Please check back next term or subscribe to receive notifications of future course offerings and other opportunities to learn more about this course and related programs.
Learning Outcomes
Upon successful completion of this course, the student will be able to:
- Describe what AI and ML are.
- Identify the right solution for a specific AI problem.
- Design and implement common search algorithms in AI including heuristic search and game search trees (e.g. minimax).
- Demonstrate reasoning in the presence of incomplete and/or uncertain information (probabilistic reasoning).
- Describe ML related applications of AI.
- Practice different 'learning from examples' algorithms (e.g. decision trees, regression models, artificial neural networks, inductive inference).
- Apply AI and ML techniques to real world problems (e.g. natural language processing or computer vision).
Effective as of Fall 2023
Related Programs
Artificial Intelligence (COMP 8085) is offered as a part of the following programs:
- Indicates programs accepting international students.
- Indicates programs eligible for students to apply for Post-graduation Work Permit (PGWP).
School of Computing and Academic Studies
- Applied Computer Science (Database Option)
Bachelor of Science Full-time/Part-time
- Applied Computer Science (Games Development Option)
Bachelor of Science Full-time
- Applied Computer Science (Human Computer Interface Option)
Bachelor of Science Part-time
- Applied Computer Science (Network Security Administration Option)
Bachelor of Science Part-time
- Applied Computer Science (Network Security Applications Development Option)
Bachelor of Science Full-time/Part-time
- Applied Computer Science (Wireless and Mobile Applications Development Option)
Bachelor of Science Part-time
Programs and courses are subject to change without notice.