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Description

This course explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation. Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning as they incorporate them into their own Python programs. By course’s end, students emerge with experience in libraries for machine learning as well as knowledge of artificial intelligence principles that enable them to design intelligent systems of their own.

Prerequisites

CSCI S-50, CS50x, or at least one year of experience with Python.

Table of Contents

  1. Watch Lecture 0 after 2024-06-24T00:00:00-04:00.
  2. Complete Quiz 0, due 2024-06-27T23:59:00-04:00.
  3. Attend section, live and with webcam and audio enabled (per sections’ norms).
  4. Optionally attend office hours.
  5. Work on Project 0, due 2024-06-30T23:59:00-04:00.

Knowledge

  1. Watch Lecture 1 after 2024-07-01T00:00:00-04:00.
  2. Complete Quiz 1, due 2024-07-04T23:59:00-04:00.
  3. Attend section, live and with webcam and audio enabled (per sections’ norms).
    • Note that, due to the holiday, there is no Thursday section this week!
  4. Optionally attend office hours.
  5. Work on Project 1, due 2024-07-07T23:59:00-04:00.

Uncertainty

  1. Watch Lecture 2 after 2024-07-08T00:00:00-04:00.
  2. Complete Quiz 2, due 2024-07-11T23:59:00-04:00.
  3. Attend section, live and with webcam and audio enabled (per sections’ norms).
  4. Optionally attend office hours.
  5. Work on Project 2, due 2024-07-14T23:59:00-04:00.
    • Note that Project 2 has two different options for you to choose from; you may only submit one, not both.

Optimization

  1. Watch Lecture 3 after 2024-07-15T00:00:00-04:00.
  2. Complete Quiz 3, due 2024-07-18T23:59:00-04:00.
  3. Attend section, live and with webcam and audio enabled (per sections’ norms).
  4. Optionally attend office hours.
  5. Work on Project 3, due 2024-07-21T23:59:00-04:00.

Learning

  1. Watch Lecture 4 after 2024-07-22T00:00:00-04:00.
  2. Complete Quiz 4, due 2024-07-25T23:59:00-04:00.
  3. Attend section, live and with webcam and audio enabled (per sections’ norms).
  4. Optionally attend office hours.
  5. Work on Project 4, due 2024-07-28T23:59:00-04:00.

Neural Networks

  1. Watch Lecture 5 after 2024-07-29T00:00:00-04:00.
  2. Complete Quiz 5, due 2024-08-01T23:59:00-04:00.
  3. Attend section, live and with webcam and audio enabled (per sections’ norms).
  4. Optionally attend office hours.
  5. Work on Project 5, due 2024-08-04T23:59:00-04:00.

Language

  1. Watch Lecture 6 after 2024-08-02T00:00:00-04:00.
  2. Complete Quiz 6, due 2024-08-05T23:59:00-04:00.
  3. Attend section, live and with webcam and audio enabled (per sections’ norms).
  4. Optionally attend office hours.
  5. Work on Project 6, due 2024-08-09T23:59:00-04:00.
    • As a reminder, Project 6 may not be turned in late, per the syllabus. The semester ends at the moment the project is due, and we are not allowed for any reason to accept late work after the semester ends.