A course is the basic teaching unit, it's design as a medium for a student to acquire comprehensive knowledge and skills indispensable in the given field. A course guarantor is responsible for the factual content of the course.
For each course, there is a department responsible for the course organisation. A person responsible for timetabling for a given department sets a time schedule of teaching and for each class, s/he assigns an instructor and/or an examiner.
Expected time consumption of the course is expressed by a course attribute extent of teaching. For example, extent = 2 +2 indicates two teaching hours of lectures and two teaching hours of seminar (lab) per week.
At the end of each semester, the course instructor has to evaluate the extent to which a student has acquired the expected knowledge and skills. The type of this evaluation is indicated by the attribute completion. So, a course can be completed by just an assessment ('pouze zápočet'), by a graded assessment ('klasifikovaný zápočet'), or by just an examination ('pouze zkouška') or by an assessment and examination ('zápočet a zkouška') .
The difficulty of a given course is evaluated by the amount of ECTS credits.
The course is in session (cf. teaching is going on) during a semester. Each course is offered either in the winter ('zimní') or summer ('letní') semester of an academic year. Exceptionally, a course might be offered in both semesters.
The subject matter of a course is described in various texts.
MI-MVI.16 Computational Intelligence Methods Extent of teaching: 2P+1C Instructor: Completion: Z,ZK Department: 18105 Credits: 5 Semester: Z Annotation:
Students will understand methods and techniques of computational intelligence that are mostly nature-inspired, parallel by nature, and applicable to many problems. They will learn how these methods work and how to apply them to problems related to data mining, control, intelligen games, optimizations, etc.
Lecture syllabus:
1. Introduction to computational intelligence, its uses. 2. Algorithms of machine learning. 3. Neural networks. 4. Evolutionary algorithms, evolution of neural networks. 5. [3] Computational intelligence methods: for clustering, for classification, for modeling and prediction. 6. Fuzzy logic. 7. Swarms (PSO, ACO). 8. Ensemble methods. 9. Inductive modeling. 10. Quantum and DNA computing. 11. Case studies, new trends. Seminar syllabus:
1. Introduction, getting acquainted with tools. 2. Introduction to the problems. 3. Course project assignment. 4. Consultations. 5. Consultations. 6. Project checkpoint. 7. Consultations. 8. Consultations. 9. Project checkpoint. 10. Consultation. 11. Report check. 12. Project presentations, workshop. 13. Project presentations, workshop. 14. Project presentations, workshop, assessment. Literature:
1. Konar, A. ''Computational Intelligence: Principles, Techniques and Applications''. Springer, 2005. ISBN 3540208984. 2. Bishop, C. M. ''Neural Networks for Pattern Recognition''. Oxford University Press, 1996. ISBN 0198538642. Requirements:
BI-ZUM - Introduction to artificial intelligence
Informace o předmětu a výukové materiály naleznete na https://courses.fit.cvut.cz/MI-MVI/ The course is also part of the following Study plans:
Study Plan Study Branch/Specialization Role Recommended semester MI-WSI-ISM.2016 Web and Software Engineering V 2 MI-NPVS.2016 Design and Programming of Embedded Systems V 2 MI-PB.2016 Computer Security V 2 MI-PSS.2016 Computer Systems and Networks V 2 MI-SP-SP.2016 System Programming V 2 MI-WSI-SI.2016 Web and Software Engineering V 2 MI-ZI.2016 Knowledge Engineering PO 2 MI-WSI-WI.2016 Web and Software Engineering V 2 MI-SPOL.2016 Unspecified Branch/Specialisation of Study VO 2 MI-ZI.2018 Knowledge Engineering PO 2 MI-SP-TI.2016 System Programming PZ 3 MI-SP-TI.2016 System Programming V 2
Page updated 25. 4. 2024, semester: Z,L/2023-4, Z/2019-20, Z/2024-5, L/2022-3, Z/2020-1, Z,L/2021-2, L/2020-1, Z/2022-3, L/2019-20, Send comments to the content presented here to Administrator of study plans Design and implementation: J. Novák, I. Halaška