• Course code:63266
  • Credits:6
  • Semester: winter
  • Contents

Lecture topics:

  1. Introduction to intelligent systems and data science
  2. Nature inspired computing (genetic algorithms, genetic programming)
  3. Introduction to predictive modelling
  4. Bias, variance and overfitting
  5. Representation learning and feature selection
  6. Ensemble methods
  7. Kernel methods
  8. Neural networks: architectures, backpropagation, deep neural networks
  9. Model inference and explanation
  10. Natural language processing: text representation, information extraction, text classification, semantic similarity
  11. Reinforcement learning: basic approaches and algorithms, Q learning, TD learning, deep RL
  • Study programmes
  • Distribution of hours per semester
45
hours
lectures
24
hours
laboratory work
6
hours
tutorials
  • Professor
Prof. dr. Marko Robnik Šikonja
Instructor
Room:R2.06 - Kabinet
details
BK
Boshko Koloski
Teaching Assistant
Room:R2.25
details
TŠ
Assist. dr. Tadej Škvorc
Teaching Assistant
Room:R2.26 - Laboratorij LKM
details
Assist. Assist. Aleš Žagar
Teaching Assistant
Room:R2.26 - Laboratorij LKM
details