Přístupnostní navigace
E-application
Search Search Close
Course detail
FEKT-LUINAcad. year: 2016/2017
The aim of the course is to deepen knowledges and application of artificial intelligence methods. Artificial intelligence – definition, trends. Artificial neural networks, neural networks paradigms, method of backpropagation learning, Kohonen self-organizing maps, Hopfield network, RCE neural network. Knowledge-based systems, knowledge representation, problem solving, structure and activities of expert systems. Optical information processing resources of artificial inteligence. Intelligent robot.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Learning outcomes of the course unit
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Course curriculum
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Recommended reading
Classification of course in study plans
branch ML-KAM , 2 year of study, winter semester, compulsory
branch EE-FLE , 1 year of study, winter semester, compulsory
Lecture
Teacher / Lecturer
Syllabus
Exercise in computer lab