[ 536AIBA19 ] Subject AI Basics and Practical Training

Es ist eine neuere Version 2021W dieses Fachs/Moduls im Curriculum Bachelor's programme Artificial Intelligence 2023W vorhanden.
Workload Mode of examination Education level Study areas Responsible person Coordinating university
26 ECTS Accumulative subject examination B1 - Bachelor's programme 1. year Computer Science Sepp Hochreiter Johannes Kepler University Linz
Detailed information
Original study plan Bachelor's programme Artificial Intelligence 2019W
Objectives This subject covers the basic methods and the background of artificial intelligence (AI) including the history of AI and the current state of the field. Students learn the foundational concepts of and approaches to AI and the major fields within it. Basic concepts include search algorithms, knowledge representation, logical inference, reasoning with uncertain knowledge, and inductive vs. deductive reasoning.

The objective of the seminar is to teach and practice scientific methods by studying advanced topics of Artificial Intelligence. Students have to work on a certain part of the seminar topic independently, do literature research, and present and discuss the results in front of the other students.

Another objective of this subject is that students acquire practical skills in AI and are able to use major software tools. Examples are solving simple tasks in reinforcement learning, constructing a first classifier from given data, or performing clustering and PCA on simple data sets. Software tools may be Scikit-Learn, TensorFlow, PyTorch, or similar.

Subject The contents of this subject result from the contents of its courses.
Subordinated subjects, modules and lectures