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Srđan Lazendić

Postdoctoral Assistant and Researcher



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Academic year 2021/2022


In this academic year I am giving exercises for the following courses:




BaWi - Basic Mathematics
-first year bachelor in engineering-

WIBA

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.



Calculus
-first year bachelor in architecture-

CALC

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.




Mathematical Analysis
-second year bachelor in architecture-

waIII

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.





Applied Functional Analysis - TFA
-second year master in mathematics-

WIBA

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.




Probability and Statistics - WenS
-first year bachelor in engineering-

WENS

Lecturer: Gert de Cooman


Teaching language: Dutch


Content:
The intention of this course is to teach the students the basic principles and the reasoning methods of probability theory. Furthermore, we want to familiarise them with the most commonly used probabilistic and statistical techniques, and the ideas behind them. Finally, we teach them how to apply probabilistic and statistical methods using pen-and-paper methods and in Python.




Artificial Intelligence - AI
-first and second year master in engineering-

AI

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.