Czech

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Condition of petting full credit is absolut (100%) attendance in obligatory parts of lessons - the computer exercises and obtaining at least 15 points. Students are tested continuously and i tis possible to get maximum 20 points. The final written exam is rated by 70 points at maximum and the oral exam is rated by 10 points at maximum.
The computer exercises are compulsory, the properly excused missed computer exercises can be compensate.

The course aims to explain the basic concepts of artificial intelligence (such as AI, ANI, ML, AGI, and ASI), with special emphasis on artificial neural networks, knowledge systems, and computer vision.
Students who completed the course should be able to:
- explain the principles of artificial intelligence in terms of their technological applicability;
- define the paradigms of selected artificial neural networks, i.e., the perceptron, and the
backpropagation and convolutional neural networks;
- discuss and verify the setting of the parameters of a neural network;
- evaluate the usability of artificial neural networks in various target areas;
- characterize the architectures and functionalities of knowledge systems;
- create a knowledge base for the NPSCORE expert system,
- identify and select application fields to host expert systems;
- employ artificial intelligence to process optical information.

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MAŘÍK, Vladimír, ŠTĚPÁNKOVÁ, Olga, LAŽANSKÝ, Jiří a kolektiv. Umělá inteligence (1. až 6. díl) Praha: Academia 1993 - 2013. (CS)
RUSESELL, Stuart a NORVIG, Peter. Artificial Intelligence. A Modern Aproach. New Jersey: Prentice Hall 2010. 1132 s. ISBN-13: 978-0-13-604259 (EN)

DUDA, Richard, HART Peter a STORK David. Pattern Classification. New York: John Wiley & Sons, INC. 2001. 654 s. ISBN 0-471-05669-3. (EN)
SONKA, Milan, HLAVAC, Vaclav a BOYLE, Rogert. Image Processing, Analysis and Machine Vision. Toronto: Thomson, 2008. 829 s. ISBN 978-0-495-24438-7. (EN)