Course name	Number of hours				ECTS credits	Form of crediting a course
1st year 2021/22	Lecture	Practical class	Labs or Seminar	Total
1st semester
Bootcamp – introduction to mathematics (1000-317bBIM)	15	15		30	3	test
Bootcamp – introduction to machine learning 1000-317bBUM	10		10	20	3	test/ project
Ideas and informatics 1000-317bIII			30	30	3	essay/project
Statistical machine learning 1000-317bSML	30		30	60	6	E
Deep neural networks 1000-317bDNN	30		30	60	6	E
Robot control 1000-317bRC	30		30	60	6	E
Master seminar in the field of machine learning and artificial intelligence			30	30	3	G
2nd semester
Visual recognition 1000-318bVR	30		30	60	5	E/project
Natural language processing 1000-318bNLP	30		30	60	5	E/project
Reinforcement learning 1000-318bRL	30	30		60	6	E
Master seminar in the field of machine learning and artificial intelligence			30	30	2	G
Elective courses	60	60		120	12	E
2nd year 2022/23
1st semester
Explainable machine learning 1000-319bEML	15	30	15	60	6	E
Internship or study visit 1000-319bINT			160	160	6	G
Large-scale machine learning 1000-319bBML	30		30	60	6	E
Master seminar in the field of machine learning and artificial intelligence			30	30	2	talk
Team programming project in machine learning 1000-319bTML			30	30	4	project
Elective courses	30	30		60	6	E
2nd semester
Elective courses	30	30		60	6	E
General university courses*	60			60	6	E
Team programming project in machine learning 1000-319bTML			30	30	3	project
Master seminar in the field of machine learning and artificial intelligence			30	30	2 + 13	thesis
Total					120

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

* In total, in general university courses you need to collect at least 5 ECTS credits in the humanities and the social sciences.