- I teach AI in the INFODOC licence.
I teach classical symbolic AI: Problem Solving, Search Algorithms, Knowledge
Representation: Logic, Semantic Network and Frames, Expert System. I also
teach Neural Nets and Learning: Symbolic (ID3, Conceptual Learning) and Numeric
(NN, Classifier Systems).
- I teach Computer Science in the second year and the third year of Ecole
de Commerce de Solvay.
- In the second year, it is an introduction
to the computer architecture and the basic principles of computer science.
- CLICK
HERE if you want to download part of the power-point slides I rely on
during this teaching.
The students also receive training in the conception of relational data base
(create tables and relations among these tables) and some very preliminary
training in the practice of programming (variables, control instructions and
function definition)
- CLICK
HERE if you want to download the power-point slides of the course on
relational data base.
- CLICK
HERE if you want to download the power-point slides of exercices and
their correction on relational data base.
- CLICK
HERE if you want to download a pdf document covering my introduction
to programming with Python.
- CLICK
HERE if you want to download a pdf document containing the exams of
previous years.
- In the third year, it is an introduction
to programming and I rely on Object-Oriented Programming and JAVA.
- CLICK
HERE if you want to download my power-point course.
- CLICK HERE to see
the kind of programming exercice I ask my students to be able to realize
- You should go to the site of
Nicolas Van Zeebroek for complementary and interesting stuff mainly
for preparation to the programming intensive week.
- I teach Object-Oriented programming languages in the third year of Faculte
Polytechnique de l'ULB and AI in the fifth year
- CLICK HERE
if you want to download my power-point introduction to OO Concepts.
- In the third year, it is an introduction
to OO programming: class, objects, class interaction, generalisation, polymorphism,
encapsulation, distributed object, using and computing in C++, java, UML,
RMI, Corba, etc...
- In the fifth year, it is an introduction
to numerical methods in AI for learning: reinforcement learning, symbolic
learning, neural nets, data mining, genetic algorithms, also methods for
simulating and controlling complex systems (non-linear processes, biological
networks) + AI methods for managing good reasoning and problems of uncertainty.
You can download the ppt slides of the courses:
- first course: Introduction to numerical methods
CLICK HERE
- second course: Introduction to Neural Nets
CLICK HERE
- third course: Introduction to Data Mining
CLICK HERE
- fourth course: Introduction to Reinforcement Learning
CLICK HERE
- fifth course: Introduction to Genetic Algorithms
CLICK HERE
- sixth course: Introduction to Networks
CLICK HERE
- seventh course: Introduction to ants algorithms
CLICK HERE
- eigth course: Introduction to artificial immune systems
CLICK HERE