CPSC 383: Explorations in Artificial Intelligence and Machine Learning (Fall 2025)

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 Wednesday, September 3rd, 2025
  • Last day to drop is Thursday, September 11th, 2025
  • Last day to add is Friday, September 12th, 2025
  • Lectures end and last day to withdraw is Friday, December 5th, 2025
  • CPSC 383 L01 MonWedFri 10:00-10:50 BI 186

Tutorials

  • Tutorials will begin on Tuesday, September 9th, 2025
  • The main goals of the tutorials will be to help you in more deeply understanding the concepts presented in the lectures through in-person worksheets and help for your assignments.
  • CPSC 383 T01 TueThu 09:00-09:50 MS 239
  • CPSC 383 T02 TueThu 10:00-10:50 MS 239
  • CPSC 383 T03 TueThu 16:00-16:50 MS 239
  • CPSC 383 T04 TueThu 12:00-12:50 MS 239
  • CPSC 383 T05 TueThu 13:00-13:50 MS 239
  • CPSC 383 T06 TueThu 14:00-14:50 MS 239

Office Hours

  • MonWed 11:00-11:50 ICT 712 or setup via email (info in D2L Content)

Important Dates

  • Term Break: Sunday-Saturday, November 9-15th, 2025. (no lectures or tutorials)
  • University Closed for Truth and Reconciliation Day Monday, September 30th, 2025. (No lecture/office hours)
  • University Closed for Thanksgiving Day Monday, October 13th, 2025. (No lecture/office hours)
  • University Closed for Remembrance Day Monday, November 11th, 2025. (No office hours)

Textbook Resources (!!Extremely Optional!!)

  • Artificial Intelligence: A Modern Approach 4e
    • 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
  • Topics
    • Part 1: AI and Search
      • Introduction
      • History and Definitions
      • Agents
      • Search
      • Path-Finding
      • Games
      • Advanced Search
      • Ethics, Legality & Society
    • Part 2: Multi-Agent Systems and Machine Learning
      • Multi-Agent Systems
        • Definitions
        • Communication
        • Planning
        • Game Theory
        • Decision Making Models
        • Voting
        • Auctions
      • Machine Learning
        • Definitions
        • Clustering
        • Association Rule Mining
        • Decision Trees and Random Forests
        • Reinforcement Learning & Multi-Armed Bandit Problems
    • Part 3: Neural Networks
      • Introduction to Machine Learning
      • Model Fitting
      • Neural Networks
      • Data Encoding
      • Convolutional Neural Networks
      • Generative Neural Networks
      • Natural Language Processing
      • Agentic AI

Technology

  • Python 3 (labs -> 3.13.5)
    • Python 3.13.5 or newest version Python 3.13.6 can be found Here
    • Most likely pick one of:
      • Visual Studio Code IDE Here
      • Pycharm IDE Here (Should be able to use ucalgary email to access Professional version as student)
    • Notebook Python solutions:
      • Google Colab: interactive notebooks for python here
      • Jupyter IPython Notebooks (can run these in Pycharm or otherwise install on your own system) Here

Quizzes/Participations

  • Quizzes
    • 6 times through-out semester
    • 15-30 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, September 26th, 2025 10:00 (10:00 AM)
    • Submission of corresponding reflection to D2L by October 3rd, 2025 23:59 (11:59 PM)
  • Discussion/Reflection 2
    • In-Class Date: Friday, October 24th, 2025 10:00 (10:00 AM)
    • Submission of corresponding reflection to D2L by October 31st, 2025 23:59 (11:59 PM)
  • Discussion/Reflection 3
    • In-Class Date: Friday, November 28th, 2025 10:00 (10:00 AM)
    • Submission of corresponding reflection to D2L by December 5th, 2025 23:59 (11:59 PM)

Aegis

  • Documentation

Assignments

  • Assignment 1
    • Due Date: Friday, October 3rd, 2025 23:59 (11:59 PM)
    • Description: Individual Assignment
    • Topics: Search/Path-Finding
  • Assignment 2
    • Due Date: Friday, November 7th, 2025 23:59 (11:59 PM)
    • Description: Individual Assignment
    • Topics: Machine Learning/Image Recognition
  • Assignment 3
    • Due Date: Tuesday, December 5th, 2025 23:59 (11:59 PM)
    • Description: Team Assignment
    • Topics: Mult-Agent Systems/Communication/Planning