COSC 4600/5600: Fundamentals of Artificial Intelligence

This is the official webpage for COSC 4600/5600: Fundamentals of Artificial Intelligence for Fall 2017.

Location: 412 Cudahy Hall

Time: TueTh 5:00-6:15 pm

Office hours: TueTh 3:30-5:00 pm

You will find the syllabus here.


  • jupyter master website (url)
  • anaconda python distribution (url)
  • github website (url) and desktop app (url)
  • jupyter notebook best practices for data science (url)
  • class github repo (url)
  • icwsm aaai repo (url)


aug 29: introduction to the course

aug 31: introduction to social networks; read: chapter 1

sep 05: types of social networks; introduction to centrality metrics; read: centrality metrics

sep 07: more centrality metrics

sep 12: introduction to clustering; k-means and dbscan; read: easy book chapter

sep 14: introduction to clustering; spectral and graph based clustering

sep 19: introduction to naive bayes; read: really easy introduction

sep 21: introduction to logistic regression; read: slightly more mathy chapter

sep 26: decision trees and random forests; read: cart + rfs

sep 28: network clusters, components cliques etc. read: good read; better read

oct 03: the preferential attachment model; read: mathy version; less mathy version

oct 5: compartmental models – the simple sir; read: chapter 21

oct 10: initial project presentations;

oct 12: small world networks; read: the book; the og; wolfram

oct 17: introduction to game theory; read: chapter 6

oct 19: no class, fall break

oct 24: guest lecture by Alex Czachor, Senior Data Scientist, Northwestern Mutual

oct 26: no class because of intel deep learning seminar makeup

oct 31: guest lecture by Nithin Ramachandran, Director, Data Science, Direct Supply

nov 02: guest lecture by RJ Nowling, Lecturer and Data Science Engineer, Marquette University

nov 07: nash equilibria, coordination games and multiple equilibria; readings: chapter 6

nov 09: introduction to markets and matching markets; readings: chapter 10

nov 13: more matching markets; readings: chapter 10 , more mathy stuff at duke

nov 15: modeling matching markets; readings: chapter 10

nov 21: thanksgiving! no class!

nov 23: thanksgiving! no class!

nov 28: final project presentations!

nov 30: introduction to information cascades; readings: chapter 16

dec 05: no class, away to nsf panel;

dec 07: modeling information cascades; readings: chapter 16