Techniques of Artificial Intelligence
From February 13th, 2016 on Mondays from 10 am till noon at the VUB campus in Room E 006. http://www.vub.ac.be/sites/vub/files/campus/plans_VUB_Etterbeek_NL_2015_...
Learn to apply AItechniques on real life engineering case studies.
Basics of statistics and programming.

Introduction to AI + state representation and search

Learning of concepts (version spaces and decision trees)

Datamining

Reinforcement Learning

Bayesian Learning

Neural Networks

Evaluation of hypotheses

Computational learning theory

Heuristic Optimisation
VUB/ULB students: Exam+Project.
Information on the project will be given during the first and last exercise lecture.
VUB students (optional for ULB students): Additional assignment related to the exercises sessions, as a preparation for the project.
Lectures
 06/02 No class!
 13/02 Introduction to AI
 20/02 State space search (students knowing this material (see slides) don't have to attend)
 27/02 Concept learning
 06/03 Decision trees and Clustering
 13/03 Metaheuristics and Genetic Algorithms
 20/03 Evaluation of hypothesis and computational learning theory
 27/03 Reinforcement Learning
 24/04 Neural networks 1
 08/05 Neural networks 2
 15/05 Data, Text and Graph mining (exceptionally till 1pm)
Excercises
* For the VUB students on Mondays from 1:30pm to 4:30pm in room D3.14 in weeks 23, 25, 2728, 32, 3436.
* For the ULB students and the VUB students with sufficient programming skills : Wednesdays February 22 and March 8, 15, 22 and 29 , from 12.15am to 2pm at C4.219 (Building C, 4th floor , 87 av. Adolphe Buyl Campus Solbosch ULB, http://www.ulb.ac.be/campus/solbosch/plan.html )
Handbook Tom Mitchell ( slides)
Handbook Artificial Intelligence: A Modern Approach, by Russel and Norvig (http://aima.cs.berkeley.edu/)
Handbook The essence of Artificial Intelligence, by Alison Cawsey (http://www.macs.hw.ac.uk/~alison/essence.html) (Chapters 14)
Example Exams