Throughout the course, participants will gain a fundamental understanding of RL, acquiring the ability to apply learned principles to various scenarios. Advanced techniques such as policy gradients and actor-critic methods will also be explored to deepen understanding of modern approaches in Reinforcement Learning. Through practical examples, participants will have the opportunity to apply acquired knowledge to real-world problems.
At the end of the course, participants will be equipped to analyze complex problems, identify appropriate RL techniques, and apply them in practice. This interactive training will provide a solid foundation for further exploration and application of Reinforcement Learning in various fields, from robotics to finance.
The lecturers will be professors from the Faculty of Technical Sciences in Novi Sad, and the whole course is supported by SMIC UNIDO.
