CPSC 383: Explorations in Artificial Intelligence and Machine Learning (Winter 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 has been converted to inactive mode. (some links should no longer be expected to work)
  • More recent offering can be found here.

Lectures

  • Lectures begin on Monday, January, 13th, 2025
  • Last day to drop is Thursday, January 23rd, 2025
  • Last day to add is Friday, January 24th, 2025
  • Lectures end and last day to withdraw is Friday, April 11th, 2025
  • CPSC 383 L01 MonWedFri 12:00-12:50

Tutorials

  • Tutorials will begin on Monday, January 20th, 2025
  • The main goals of the tutorials will be to help you in more deeply understanding the concepts presented in the lectures (providing more examples) and with your assignments.
  • CPSC 383 T01 MonWed 13:00-13:50
  • CPSC 383 T02 MonWed 14:00-14:50
  • CPSC 383 T03 TueThu 08:00-08:50
  • CPSC 383 T04 TueThu 09:00-09:50
  • CPSC 383 T05 TueThu 13:00-13:50

Office Hours

  • MonTue 13:00-13:50 ICT 712 or setup via email (info in D2L Content)

Important Dates

  • Term Break: Sunday-Saturday, February 16-22nd, 2025. (no lectures or tutorials)
  • University Closed for Alberta Family Day Monday, February 17th, 2025. (No lecture/office hours)

Textbook Resources (!!Extremely Optional!!)

  • Artificial Intelligence: A Modern Approach 5e
    • Author: Russell Norvig
    • ISBN: 9780134610993
    • Optional: For those who appreciate another resource. Taught material diverges from this source.
    • Version 3e/4e 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 (slides in D2L)
    • Part 1: AI and Search
      • Introduction
      • History and Definitions
      • Agents
      • Search
      • Path-Finding
      • Games
      • Advanced Search
      • Ethics, Legality & Society
    • Part 2: Machine Learning and Neural Networks
      • Introduction to Machine Learning
      • Model Fitting
      • Data Encoding
      • Connectionist AI
      • Neural Networks
      • Convolutional Neural Networks
      • Generative Neural Networks
      • Neural Networks for Natural Language Processing
    • Part 3: Selected other areas of AI and Machine Learning.
      • Multi-Agent Systems
      • Communication
      • Planning
      • Game Theory
      • Voting
      • Stakeholders
      • Clustering
      • Association Rule Mining
      • Decision Trees
      • Multi-Armed Bandit Problems

Technology

  • Python 3 (labs -> 3.12.4)
    • Python 3.12.4 or newest version Python 3.12.5 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
ALL DATES HERE ARE PRELIMINARY. D2L DATES TAKE PRECEDENCE.

Quizzes/Participations

  • Quizzes
    • 6 times through-out semester
    • 15-30 minute D2L quizzes.
    • Best 5 of 6 count.
  • Participations
    • 12 times through-out semester
    • Done in tutorials and submitted at the end for credit.
    • Best 11 of 12 count.

Discussion/Reflection

  • Discussion/Reflection 1
    • In-Class Date: Friday, January 20th, 2025 12:00
    • Submission of corresponding reflection to D2L by January 27th
  • Discussion/Reflection 2
    • In-Class Date: Friday, Febraury 28th, 2025 12:00
    • Submission of corresponding reflection to D2L by March 7th
  • Discussion/Reflection 3
    • In-Class Date: Friday, March 28th, 2025 12:00
    • Submission of corresponding reflection to D2L by April 4th

Aegis

  • Documentation

Assignments

  • Assignment 1
    • Due Date: Friday, February 7th, 2025 23:59 (11:59 PM)
    • Description: Individual Assignment
    • Topics: Search/Path-Finding
  • Assignment 2
    • Due Date: Friday, March 14th, 2025 23:59 (11:59 PM)
    • Description: Individual Assignment
    • Topics: Machine Learning/Image Recognition
  • Assignment 3
    • Due Date: Tuesday, April 8th, 2025 23:59 (11:59 PM)
    • Description: Team Assignment
    • Topics: Mult-Agent Systems/Communication/Planning