Lecturer: Hennie De Schepper
Teaching language: Dutch
Content:
The aim of this course is threefold: (1) to rehearse the fundamental mathematics knowledge for starting academic engineering studies;
(2) to make clear what is the expected mathematics level in academic engineering studies; (3) to establish a uniform starting level
for all students.
Lecturer: Hennie De Schepper
Teaching language: Dutch
Content:
The main aim is to teach the student how to reason in a critical, logical and structured
way, on the appropriate level of abstraction, while paying attention also to
completeness and precision.
Lecturer: Hendrik De Bie
Teaching language: Dutch
Content:
The student gains insight in solution methods for ordinary and partial differential
equations. The student also gains insight in the definition of line and surface integrals,
the underlying theoretical results and their practical computation.
Lecturer: Hennie De Schepper
Teaching language: Dutch
Content:
It is the aim of the course to provide insight in the basic concepts of the theory of
functions of several real variables and the application of the corresponding analysis
techniques. Moreover the students acquire skills in using these techniques and
applying them, as well as in the analytic and mathematical modelling of basic problems
from basic sciences.
Lecturer: Marián Slodička
Teaching language: Dutch
Content:
The intention of this course is to give the students an introductory but efficient matter
consisting of terms, results and methods from functional analysis.
This will be illustrated on some simplified practical applications coming from various
engineering disciplines.
The fundamental concepts of the operator and spectral theory will be explained and
applied to diverse problems.
Lecturer: Aleksandra Pižurica
Teaching language: English
Content:
The course gives an overview of the principles and modern approaches in artificial intelligence.
The focus is on intelligent agents, reasoning under uncertainty, and making rational decisions. It covers the following topics: knowledge representation,
reasoning under uncertainty, Bayesian networks, Hidden Markov Models, belief propagation, deep learning, rational agents and rational decisions as well as
visual intelligence.