Course details
This course provides an introduction to the various topics in Artificial Intelligence (AI). Topics to be covered include search, games, regression, classification and neural networks. Students will develop an understanding of the fundamentals underpinning AI applications and gain hands-on experience through the development of AI systems. Practical work in course projects focuses on developing components of AI systems as well as analyzing real-world datasets from different domains. The societal implications and ethical considerations in the design of AI systems will also be discussed.
Prerequisite(s)
- Acceptance into the Bachelor of Science in Applied Computer Science (BScACS) program OR special permission (COMP2121, MATH3042, COMP3522 or equivalent).
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 compleltion of this course, the student will be able to:
- Describe current applications of AI.
- Solve problems using uninformed, informed and adversarial search techniques.
- Explain the concepts of learning and the differences between unsupervised, supervised and reinforcement learning.
- Explain the basics of different regression, classification and neural network techniques.
- Apply machine learning techniques and algorithms to datasets.
- Perform model selection and parameter tuning of machine learning techniques.
- Design and develop components of AI systems.
- Identify potential applications of AI techniques to real-world problems.
- Investigate societal implications and ethics of AI.
Effective as of Winter 2022
Related Programs
Topics in Computer Programming – Artificial Intelligence (COMP 7404) is offered as a part of the following programs:
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- Applied Computer Science (Wireless and Mobile Applications Development Option)
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