After completing this course students will be able to analyse and design learning automata based solutions, and to select suitable encodings and fitness functions for specific information processing and communication tasks. Students will be able to design neural network and develop reinforcement learning techniques by using simulation tools and Java programming.
Learning Outcomes
 

•     To define concept, methods and architectures typical for machine learnings
•     To explain how machine learning operate and basic purpose
•     To apply knowledge about machine learning for telecommunication services
•     To analyze functions of machine learned components, as well as their interactions in order to find appropriate solution
•     To analyze organization of machine learned model
•     To define basic components for realisation of needed function by machine learning
•     To create machine learned models including various types of recognition and self-adaptation
•     To evaluate and assess solutions based on different methods of machine learning

Type of methodology: Combination of lecture and hands-on

Paid training activity for participants: Yes, for some only

Participants prerequisite knowledge: C/C++

Language: English and Croatian