Techniques of Artificial Intelligence


From February 13th, 2016 on Mondays from 10 am till noon at the VUB campus in Room E 006.

External lecturer: 
External assistant: 

Learn to apply AI-techniques 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.

The exam is open book, however no laptops or mobile phones are allowed.

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.





  • 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)



* For the VUB students on Mondays from 1:30pm to 4:30pm in room D3.14  in weeks 23, 25, 27-28, 32, 34-36.

* 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,  )








Handbook Tom Mitchell ( slides)

Handbook Artificial Intelligence: A Modern Approach, by Russel and Norvig (

Handbook The essence of Artificial Intelligence, by Alison Cawsey ( (Chapters 1-4)

Tutorial for Data Clustering


Example Exams

June 2012

June 2011