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Course info
KKY / ROSZ
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Course description
Department/Unit / Abbreviation
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KKY
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ROSZ
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Academic Year
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2023/2024
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Academic Year
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2023/2024
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Title
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Decision Systems
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Form of course completion
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State Final Exam
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Form of course completion
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State Final Exam
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Accredited / Credits
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Yes,
0
Cred.
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Type of completion
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Oral
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Type of completion
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Oral
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Time requirements
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Course credit prior to examination
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Yes
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Course credit prior to examination
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Yes
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Included in study average
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YES
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Language of instruction
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Czech
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Occ/max
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Summer semester
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0 / -
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0 / -
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0 / -
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Included in study average
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YES
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Winter semester
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0 / -
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0 / -
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0 / -
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Repeated registration
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NO
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Repeated registration
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NO
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Timetable
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Yes
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Semester taught
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Summer semester
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Semester taught
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Summer semester
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Minimum (B + C) students
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1
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Optional course |
Yes
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Optional course
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Yes
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Language of instruction
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Czech
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Internship duration
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0
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No. of hours of on-premise lessons |
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Evaluation scale |
1|2|3|4 |
Periodicity |
každý rok
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Evaluation scale for credit before examination |
S|N |
Periodicita upřesnění |
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Fundamental theoretical course |
No
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Fundamental course |
No
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Fundamental theoretical course |
No
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Evaluation scale |
1|2|3|4 |
Evaluation scale for credit before examination |
S|N |
Substituted course
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None
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Preclusive courses
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N/A
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Prerequisite courses
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KKY/SUR and KKY/ZSI
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Meet all prerequisites before registering
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NO
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Informally recommended courses
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N/A
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Courses depending on this Course
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N/A
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Histogram of students' grades over the years:
Graphic PNG
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XLS
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Course objectives:
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The main aim of the state exam is to check, that the student
- successfully managed knowledge in machine learning, pattern recognition, problem solving and signal processing
- knows to actively use the analytical and numerical methods in this fields
- has fundamental theoretical knowledge and professional skills, which will use further in his/her profession or within doctoral study of given specialization.
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Requirements on student
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Topics of the final examination are specified by subjects from the set: KKY/SUR, KKY/ZSI. Corresponding questions are announced annually by department of cybernetics.
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Content
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Topics of the final examination are announced annually by department of cyberneticscs.
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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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Extending:
Kotek, Zdeněk, Mařík, Vladimír. Metody rozpoznávání a jejich aplikace. Academia, Praha, 1993. ISBN 80-200-0297-9.
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Extending:
Duda, R.O., Hart, P.E., Stork, D.G. Pattern Classification. Wiley, 2000. ISBN 978-0-471-05669-0.
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Recommended:
Jan. Číslicová filtrace, analýza a restaurace. Brno, 2002. ISBN 80-214-2911-9.
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Recommended:
Theodoridis, S., Kouroumbas, K. Pattern recognition. Elsevier, 2008. ISBN 978-1-597-49272-0.
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Recommended:
Bishop, C.M. Pattern Recognition and Machine Learning. Springer, 2006. ISBN 978-0387-31073-2.
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Recommended:
Mařík V. a kol. Umělá inteligence 1. Academia, Praha, 1993. ISBN 80-200-0496-3.
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Recommended:
Uhlíř, Jan; Sovka, Pavel; Čmejla, Roman. Úvod do číslicového zpracování signálů. Praha : Vydavatelství ČVUT, 2003. ISBN 80-01-02799-6.
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On-line library catalogues
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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: |
Students must meet all prerequisites of the curriculum field Control and Decision Systems, guaranteed by the Department of cybernetics and all the conditions of Study and Examination Regulations of the University of West Bohemia in Pilsen. |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
Successful handling of the final examination shows that the student while studying in sufficiently mastered all the knowledge, skills and competencies in accordance with the requirements of the degree program and specialization. |
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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 |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
Skills demonstration |
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