Course objectives:
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An overview of the application of statistical methods in technical diagnostics.
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Requirements on student
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Term assignment (MATLAB or high-level programming language). Proficiency in discussed topics.
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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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Activities
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Fields of study
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Guarantors and lecturers
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Literature
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Time requirements
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All forms of study
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Activities
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Time requirements for activity [h]
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Graduate study programme term essay (40-50)
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40
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Preparation for comprehensive test (10-40)
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21
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Contact hours
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65
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Preparation for an examination (30-60)
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30
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Total
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156
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Prerequisites
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Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
znát alespoň jeden programovací nebo skriptovací jazyk či SW nástroj typu MATLAB |
to have basic knowledge of mathematical statistics |
Skills - students are expected to possess the following skills before the course commences to finish it successfully: |
navrhnout algoritmus |
napsat program řešící matematickou úlohu |
analyzovat problém |
Competences - students are expected to possess the following competences before the course commences to finish it successfully: |
N/A |
N/A |
N/A |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
to apply knowledge of statistical methods of technical diagnostics and its application in real situations.
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mít základní přehled o metodách strojového učení |
Skills - skills resulting from the course: |
použít algoritmy statistické indukce k řešení praktické úlohy |
umět ověřit správnost získaných výsledků |
Competences - competences resulting from the course: |
N/A |
N/A |
N/A |
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Assessment methods
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Knowledge - knowledge achieved by taking this course are verified by the following means: |
Oral exam |
Test |
Seminar work |
Skills - skills achieved by taking this course are verified by the following means: |
Oral exam |
Written exam |
Test |
Competences - competence achieved by taking this course are verified by the following means: |
Oral exam |
Test |
Seminar work |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture |
Lecture supplemented with a discussion |
Practicum |
Skills - the following training methods are used to achieve the required skills: |
Practicum |
Individual study |
Competences - the following training methods are used to achieve the required competences: |
Lecture |
Practicum |
Discussion |
One-to-One tutorial |
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