Studienhandbuch | Artificial Intelligence

Inhalt

Workload	Mode of examination	Education level	Study areas	Responsible person	Coordinating university
12 ECTS	Structure	M - Master's programme	Computer Science	Johannes Kofler	Johannes Kepler University Linz

Detailed information
Original study plan	Master's programme Electronics and Information Technology (ELIT) 2022W
Objectives	Mastering and application of in-depth and specialized knowledge in the subject of "Artificial Intelligence". Ability to analyze and develop ideas and concepts for solving scientific problems in the field of "Artificial Intelligence". Subject-related preparation for the master's thesis.
Subject	The content of teaching results from the content of the individual courses.

Subordinated subjects, modules and lectures
UE Machine Learning: Supervised Techniques
VL Machine Learning: Supervised Techniques
UE Machine Learning: Unsupervised Techniques
VL Machine Learning: Unsupervised Techniques
UE Deep Learning and Neural Nets II
VL Deep Learning and Neural Nets II
UE Deep Learning and Neural Nets I
VL Deep Learning and Neural Nets I
UE LSTM and Recurrent Neural Nets
VL LSTM and Recurrent Neural Nets
UE Theoretical Concepts of Machine Learning
VL Theoretical Concepts of Machine Learning