Differences

This shows you the differences between two versions of the page.

--- courses:be5b33kui:start [2024/02/13 10:39]
xposik
+++ courses:be5b33kui:start [2024/02/16 15:12]
dantuswa
@@ Line 3: / Line 3: @@
 Lectures: [[https://petrposik.github.io|Petr Pošík]], [[http://cmp.felk.cvut.cz/~svoboda|Tomas Svoboda]]
-Labs: [[https://mrs.felk.cvut.cz/members/research-fellows/swati-dantu|Swati Dantu]]
+Labs: [[https://mrs.felk.cvut.cz/members/phdstudents/swati-dantu|Swati Dantu]]
 The course introduces the students to the field of artificial intelligence and gives the necessary basis for designing machine control algorithms. It advances the knowledge of state space search algorithms by including uncertainty in state transitions. Students are introduced into reinforcement learning for solving problems when the state transitions are unknown. Bayesian decision task introduces supervised learning. Learning from data is demonstrated on a linear classifier. Students practice the algorithms in computer labs.
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 <WRAP important round 100%>
-**The course runs in a hybrid regime.**
+**The course runs in a hybrid regime.** The lectures and lab sessions for online participants are streamed and recorded via BigBlueButton in BRUTE. Students enrolled in EECS or other regular presence study programs at CTU are expected to physically attend lectures/labs.
 </WRAP>
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   * [[courses:be5b33kui:labs:start|]]
   * [[courses:be5b33kui:literature|]]
-  * [[https://www.fel.cvut.cz/cz/education/rozvrhy-ng.B222/public/html/predmety/43/58/p4358106.html|schedule 2022/2023]]
+  * [[https://intranet.fel.cvut.cz/cz/education/rozvrhy-ng.B232/public/html/predmety/43/58/p4358106.html|schedule 2023/2024]]