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Lecturer(s)
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Čechura Pavel, Ing. PhD.
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Škorpil Clemens, prof. Ing. Ph.D.
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Course content
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Mathematical diagnostic methods: statistical decision problems, classification, feature selection, estimation, approximation. Artificial intelligence methods applicable to diagnostics - pattern recognition and their use in diagnostic and decision making processes. Engineering approach to the implementation of technical and medical diagnostic systems, feasibility studies, implementation of diagnostic systems in industry, life cycle of diagnostic systems with regard to their development and maintenance. Examples of technical and medical diagnostic systems.
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Learning activities and teaching methods
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Lecture
- Graduate study programme term essay (40-50)
- 40 hours per semester
- Preparation for an examination (30-60)
- 30 hours per semester
- Contact hours
- 65 hours per semester
- Preparation for comprehensive test (10-40)
- 21 hours per semester
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| prerequisite |
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| Knowledge |
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| znát alespoň jeden programovací nebo skriptovací jazyk či SW nástroj typu MATLAB |
| to have basic knowledge of mathematical statistics |
| Skills |
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| navrhnout algoritmus |
| napsat program řešící matematickou úlohu |
| analyzovat problém |
| Competences |
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| N/A |
| N/A |
| N/A |
| learning outcomes |
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| Knowledge |
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| to apply knowledge of statistical methods of technical diagnostics and its application in real situations. |
| mít základní přehled o metodách strojového učení |
| Skills |
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| použít algoritmy statistické indukce k řešení praktické úlohy |
| umět ověřit správnost získaných výsledků |
| Competences |
|---|
| N/A |
| N/A |
| N/A |
| teaching methods |
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| Knowledge |
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| Lecture |
| Lecture supplemented with a discussion |
| Practicum |
| Skills |
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| Practicum |
| Individual study |
| Competences |
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| Lecture |
| Practicum |
| Discussion |
| One-to-One tutorial |
| assessment methods |
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| Knowledge |
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| Oral exam |
| Test |
| Seminar work |
| Skills |
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| Oral exam |
| Written exam |
| Test |
| Competences |
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| Oral exam |
| Test |
| Seminar work |
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Recommended literature
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Duda. O. Pattern Classification, 2nd Edition. 2004. ISBN 978-0-471-70350-1.
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Hátle, Jaroslav; Likeš, Jiří. Základy počtu pravděpodobnosti a matematické statistiky. Praha : SNTL, 1974.
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Vapnik, Vladimir N. Statistical learning theory. New York : John Wiley & Sons, Inc., 1998. ISBN 0-471-03003-1.
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