Lectures

You can download the lectures here. We will try to upload lectures prior to their corresponding classes.

• Lecture-01
  About: Introduction to AI: Why this course?
  [slides]
  

  Suggested Readings:

  • “Chapter 1: Introduction”, AI a Modern Approach, S. Russel and R. Norvig.
  • “From So Simple a Beginning”: Species of Artificial Intelligence, Nigel Shadbolt, Daedalus, 2022; 151 (2): 28–42.
  • “On Computable Numbers, with an application to the Entscheidungsproblem”, Alan Turing, Proc. London Mathematical Soc., 1937.
  • “Computing Machinery and Intelligence”, Alan Turing, Mind, 1950.
• Lecture-02
  About: Review of breakthroughs and introduction to AI agents
  [slides]
  

  Suggested Readings/Viewings:

  • “A Golden Decade of Deep Learning: Computing Systems and Applications”, Jeffrey Dean, Daedalus, 2022; 151 (2): 58–74 (Paper).
  • “Genius Makers: The Mavericks Who Brought A.I. to Google, Facebook, and the World”, Cade Metz, Dutton, 2021 (Book).
  • “AlphaGo - The Movie”, Full award-winning documentary, YouTube (Video).
• Lecture-03
  About: PEAS Framework to build AI agents
  [slides]
  

  Suggested Readings:

  • “Chapter 2: Intelligent Agents”, AI a Modern Approach, S. Russel and R. Norvig.
• Lecture-04
  About: Problem Solving by searching: Introduction
  [slides]
  

  Suggested Readings:

  • “Chapter 3: Solving Problems by Searching”, AI a Modern Approach, S. Russel and R. Norvig.
• Lecture-07
  About: Problem Solving by searching: Uninformed search
  [slides]
  

  Suggested Readings:

  • “Chapter 3: Solving Problems by Searching”, AI a Modern Approach, S. Russel and R. Norvig.
• Lecture-08
  About: Problem Solving by searching: Informed and beyond classical search
  [slides]
  

  Suggested Readings:

  • “Chapter 3: Solving Problems by Searching”, AI a Modern Approach, S. Russel and R. Norvig.
  • “Chapter 4: Beyond Classical Search”, AI a Modern Approach, S. Russel and R. Norvig.
• Lecture-09
  About: Problem Solving by searching: Theory to implementation
  [slides]
  
• Lecture-10
  About: Adversarial Search: Min-max and alpha-beta pruning
  [On board (no slides)]
  

  Suggested Readings:

  • “Chapter 5: Adversarial Search”, AI a Modern Approach, S. Russel and R. Norvig.
• Lecture-11
  About: Adversarial Search: More methods and the deep blue chess player
  [slides]
  

  Suggested Readings:

  • “Chapter 5: Adversarial Search”, AI a Modern Approach, S. Russel and R. Norvig.
• Lecture-12
  About: Introduction to Logic for AI
  [on board (no slides)]
  

  Suggested Readings:

  • “Chapter 7: Logial Agents (Sections 7.1 to 7.4)”, AI a Modern Approach, S. Russel and R. Norvig.
• Lecture-13
  About: Introduction to Logical Agents and Propositional Logic
  [on board (no slides)]
  

  Suggested Readings:

  • “Chapter 7: Logial Agents (Sections 7.1 to 7.4)”, AI a Modern Approach, S. Russel and R. Norvig.
• Lab-1
  About: Python implementation for traversing a maze
  [no slides]
  
• Lecture-14
  About: Discussion on AI: goal, evaluation, and ethics
  [Discussion in class (no slides)]
  
• Lecture-15
  About: Uncertainty: Introduction
  [on board (no slides)]
  

  Suggested Readings:

  • “Chapter 13: Quantifying uncertainty (Section 13.1)”, AI a Modern Approach, S. Russel and R. Norvig.
• Lab-2
  About: Python implementation for evaluating 6 degrees of separation for actors (using IMDB)
  [no slides]
  
• Lecture-16
  About: Uncertainty: Using language of probability
  [slides]
  

  Suggested Readings:

  • “Chapter 13: Quantifying uncertainty (Sections 13.1 to 13.4)”, AI a Modern Approach, S. Russel and R. Norvig.