| 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.
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