CPSC 383: Explorations in Artificial Intelligence and Machine Learning (Winter 2026)
A survey of artificial intelligence and machine learning tools to
cultivate an understanding of their capability, utility, and societal/ethical/legal
considerations. Popular APIs will be used to develop simple applied examples.
Announcements
- Website under construction.
Lectures
- Lectures begin on Monday, January 12th, 2026
- Last day to drop is Thursday, January 22nd, 2026
- Last day to add is Friday, January 23rd, 2026
- Lectures end and last day to withdraw is Tuesday, April 14th, 2026
- CPSC 383 L01 MonWedFri 12:00-12:50 TI 160
Tutorials
- Tutorials will begin on Monday/Tuesday, January 19th/20th, 2026
- The main goals of the tutorials will be to help you in more deeply understanding the concepts presented in the lectures through graded in-person worksheets and help for your assignments.
- CPSC 383 T01 MonWed 13:00-13:50 MS 252 Parham MoonesiSohi parham.moonesisohi@ucalgary.ca
- CPSC 383 T02 MonWed 14:00-14:50 MS 252 Mahdi FarrokhiMaleki mahdi.farrokhimaleki@ucalgary.ca
- CPSC 383 T03 TueThu 08:00-08:50 MS 252 Amin Zeinali amin.zeinali@ucalgary.ca
- CPSC 383 T04 TueThu 09:00-09:50 MS 252 Matthew McConnell matthew.mcconnell1@ucalgary.ca
- CPSC 383 T05 TueThu 13:00-13:50 MS 176 Parham MoonesiSohi parham.moonesisohi@ucalgary.ca
Office Hours
- MonWed 13:00-13:50 ICT 712 or setup via email (info in D2L Content)
Important Dates
- Term Break: Sunday-Saturday, February 15-21st, 2026. (no lectures or tutorials)
- University Closed for Alberta Family Day Monday, February 16th, 2026. (During term break, No office hours)
- University Closed for Good Friday Friday, April 3rd, 2026. (No lecture/No tutorial/No office hours)
- University Closed for Easter Monday Monday, April 6th, 2026. (No lecture/No tutorial/No office hours)
Textbook Resources (!!Extremely Optional!!)
- Artificial Intelligence: A Modern Approach 4e (2021)
- Author: Russell Norvig
- ISBN: 9780134610993
- Optional: For those who appreciate another resource. Taught material diverges from this source.
- Version 3e likely just as good for your purposes.
The due dates for the assignments can be found in the Assignments sections of this page.
Support Materials
- Course Information Sheet (Outline)
- Organization pdf
- Topics
Technology
- Python 3 (labs -> 3.13.11)
We will not be using Python 3.14.X as it does not support tensorflow- Python 3.13.11 can be found Here
- Most likely pick one of:
- Notebook Python solutions:
Quizzes/Participations
- Quizzes
- 6 times through-out semester
- 20 minute online open book D2L quizzes.
- Best 5 of 6 count.
- Participations
- 9 times through-out semester
- Require in-person attendance in tutorials. May be required to be submitted end of tutorial or sometimes in D2L.
- Best 8 of 9 count.
Discussion/Reflection
- Discussion/Reflection 1
- In-Class Date: Friday, February 6th, 2026 11:59(11:59 AM)
- Submission of corresponding reflection to D2L by February 13th, 2026 23:59 (11:59 PM)
- Discussion/Reflection 2
- In-Class Date: Friday, March 13th, 2026 11:59 (11:59 AM)
- Submission of corresponding reflection to D2L by March 20th, 2026 23:59 (11:59 PM)
- Discussion/Reflection 3
- In-Class Date: Friday, April 10th, 2026 11:59 (11:59 AM)
- Submission of corresponding reflection to D2L by April 17th, 2026 23:59 (11:59 PM)
Aegis
Assignments
- Assignment 1
- Due Date: Friday, February 13th, 2026 23:59 (11:59 PM)
- Description: Individual Assignment
- Topics: Search/Path-Finding
- Assignment Description
- Assignment 2
- Due Date: Friday, March 27th, 2026 23:59 (11:59 PM)
- Description: Team Assignment
- Topics: Mult-Agent Systems/Communication/Planning
- Assignment Description
- Assignment 3
- Due Date: Tuesday, April 14th, 2026 23:59 (11:59 PM)
- Description: Individual Assignment
- Topics: Machine Learning/Image Recognition
- Assignment Description
- Dataset