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        <description>Distance exam

In summer semester of 2020/21, the exam will have a distance form. It will be organized as follows.

Conditions for distance exam

General FEE conditions for distance exams (in Czech). 

By enrolling to the distance exam date in KOS, you confirm that you have

The exam will consist mainly of an online alternative of written test. Online oral part will follow only in unclear cases.
By enrolling to the distance exam date in KOS, you also agree with the following process:</description>
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        <description>Lectures

List of [competencies] you should have after individual lectures. (Will be updated continuously.)

Links to BBB rooms/recordings

The table below shows the links to upcoming lecture rooms/passed lecture recordings.
You can also find the links to rooms and recordings in BRUTE, or in the</description>
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        <description>Suggested study literature
“”
Videolectures

The topics of this course can be also learned from other online sources. Here we list some MOOCs with a strong connection to this course.

Andrew Ng's Machine Learning (at Coursera.org)

Pieter Abbeel's and Dan Klein's Artificial Intelligence (at edX.org)</description>
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        <description>Prerequisities

This course is designed to complement (and deepen some of) the material presented in the bachelor-level course Cybernetics and Artificial Intelligence (KUI). Despite that, you can safely attend our course even without having finished KUI. Just be warned that the AI methods and techniques covered in KUI will not be part of UI course (especially graph search methods, basics of game theory, Markov decision processes, reinforcement learning), and</description>
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        <description>Course-related links

B3M33UI Schedule 

BE3M33UI Schedule 

BE3M33UI@FEL 

BRUTE 

Discussion forum

----------</description>
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        <description>B(E)3M33UI - Artificial intelligence

The course deepens and enriches knowledge of AI gained in the bachelor course Cybernetics and Artificial Intelligence. Students will get an overview of other methods used in AI, and will get a hands-on experience with some of them. They will master other required abilities to build intelligent agents. By applying new models, they will reiterate the basic principles of machine learning, techniques to evaluate models, and methods for overfitting prevention. Th…</description>
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