Introduction to AI for Public Health
Winter 2005 Syllabus
Dr. Anthony G. Francis, Jr. - April 12, 2005 - Updates Still in Progress
Philosophy of the Course
Introduction to Artificial Intelligence with Applications to Public Health surveys the concepts, technologies and issues of artificial intelligence and how AI can be applied to improve public health outcomes. The course begins with lectures on the scope and history of artificial intelligence, then examines popular AI techniques and subject areas in a series of topical lectures. This is followed by lectures on applying AI to public health. The course concludes with a discussion of the philosophy of artificial intelligence.
Outline of the Course
This outline has been revised to reflect changes in the course.
- Week 1 (January 24): Overview
- Week 2 (January 31): Foundations
- Week 3 (February 7): Neural Networks
- Week 4 (February 14): Search
- Week 5 (February 21): Guest Lecture: Machine Learning
- Week 6 (February 28): Guest Lecture: Public Health
- Week 7 (March 7): AI Programming
- Week 8 (March 14): (break / programming help session)
- Week 9 (March 21): Language
- Week 10 (March 28): Knowledge Representation
- Week 11 (April 4): Expert Systems
- Week 12 (April 11): Data Mining
- Week 13 (April 18): Robotics and Vision
- Week 14 (April 25): Philosophy
- Week 15 (May 2): Review (tentative)
- Artificial Intelligence : A New Synthesis by Nils J. Nilsson Hardcover: 513 pages; Dimensions (in inches): 1.35 x 9.62 x 7.67 Publisher: Morgan Kaufmann; 1st edition (April 1, 1998); ISBN: 1558604677
- Machines Who Think: A Personal Inquiry into the History and Prospects of Artificial Intelligence by Pamela McCorduck Paperback: 600 pages; Dimensions (in inches): 9.00 x 1.25 x 6.00 Publisher: AK Peters, Ltd.; 2nd edition (March 1, 2004); ISBN: 1568812051
- Tests: 1 Midterm (20pts) and 1 Final (30pts)
- Essays: 2 (10pts each)
- Essay 1: Critique an Artificial Intelligence Movie or Television Show
- Essay 2: State of the Art in an Artificial Intelligence Topic
- Projects: (15pts each)
- Artificial Intelligence Programming
- Applications to Public Health
The following programs are referenced in the assignments or were used as examples in the lectures. They're by no means gems of artificial intelligence, or even really AI at all, but hopefully they will be useful for getting up to speed in Python.
A framework for playing n,m,g tic-tac-toe, for use in Assignment 1.
Simple examples using Python to process a tab-delimited file of census data.
A hyperintelligent program that can answer all your questions.
These lecture notes are also a work in progress.
- Lecture 1: Overview
- Lecture 2: Foundations of Machine Intelligence
- Lecture 3: Neural Networks and Genetic Algorithms
- Lecture 7: Programming in Python
- Lecture 9: Natural Language Understanding
- Lecture 10: Knowledge Representation
- Lecture 11: Expert Systems
- Lecture 12: Data Mining and Machine Learning
- Lecture 13: Robotics and Vision
- Lecture 14: Philosophy of AI
- Programming Resources
- Learning Python
- Dive Into Python (online)
- Artificial Intelligence
- Russel & Norvig: Artificial Intelligence: A Modern Approach
- Marvin Minsky: Society of Mind
- Hofstadter: Godel Escher Bach
- Ray Kurzweil: The Age of Spiritual Machines