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2024/05/27 14:40 xposik [Final exam]
2024/05/27 14:39 xposik [Mid-term exam assignments]
2024/05/27 14:39 xposik [Final exam]
2024/05/27 11:59 xposik [BE5B33KUI: Cybernetics and Artificial Intelligence]
2024/05/27 10:11 xposik [Final exam]
2024/02/16 15:12 dantuswa
2024/02/13 10:42 xposik [BE5B33KUI: Cybernetics and Artificial Intelligence]
2024/02/13 10:41 xposik [BE5B33KUI: Cybernetics and Artificial Intelligence]
2024/02/13 10:39 xposik
2023/02/17 07:36 external edit
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2024/05/27 14:40 xposik [Final exam]
2024/05/27 14:39 xposik [Mid-term exam assignments]
2024/05/27 14:39 xposik [Final exam]
2024/05/27 11:59 xposik [BE5B33KUI: Cybernetics and Artificial Intelligence]
2024/05/27 10:11 xposik [Final exam]
2024/02/16 15:12 dantuswa
2024/02/13 10:42 xposik [BE5B33KUI: Cybernetics and Artificial Intelligence]
2024/02/13 10:41 xposik [BE5B33KUI: Cybernetics and Artificial Intelligence]
2024/02/13 10:39 xposik
2023/02/17 07:36 external edit
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courses:be5b33kui:start [2023/02/17 07:36]
127.0.0.1
external edit
courses:be5b33kui:start [2024/05/27 14:40]
xposik
[Final exam]
Line 1:
Line 1:
====== BE5B33KUI: Cybernetics and Artificial Intelligence ======
====== BE5B33KUI: Cybernetics and Artificial Intelligence ======
-
Lectures
: [[
mailto
:
petr
.
posik@cvut
.
cz
|Petr Pošík]], [[http://cmp.felk.cvut.cz/~svoboda|Tomas Svoboda]]
+
Lecturers
: [[
https
:
//petrposik
.
github
.
io
|Petr Pošík]], [[http://cmp.felk.cvut.cz/~svoboda|Tomas Svoboda]]
-
Labs
: [[https://
usermap
.cvut.cz/
profile
/
7da4274e-aa23-40e1-b528
-
47b038a64626
|
Filipe Gama
]]
+
Lab instructors
: [[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.
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.
-
The course expects basic knowledge of probability and linear algebra. We expect that students are able to write decent computer programs in a higher level language and have basic knowledge
about
data structures. Python will be used in computer labs.
+
**Prerequisities:**
The course expects
**
basic knowledge of probability and linear algebra
**
. We expect that students are able to
**
write decent computer programs in a higher level language
**
and have
**
basic knowledge
of
data structures
**
. Python will be used in computer labs.
<WRAP important round 100%>
<WRAP important round 100%>
-
**The course
starts
in
regular contact
regime**
, but might change
to
[[courses:be5b33kui:distance_teaching|distance teaching]] if needed
.
+
**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>
</WRAP>
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* [[courses:be5b33kui:labs:start|]]
* [[courses:be5b33kui:labs:start|]]
* [[courses:be5b33kui:literature|]]
* [[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
]]
Line 35:
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==== Final exam ====
==== Final exam ====
+
+
<WRAP center round tip 60%>
+
When preparing for the exam, you can also use this [[https://docs.google.com/presentation/d/1WumcPGnL4-Ig71ncIMITjh2ZxsTa8lcUeLl-3v7IQeo/edit?usp=sharing|presentation]] prepared by K. Poláková!
+
</WRAP>
+
The final exam is worth 40 points. You need at least 18 points from the final exam to pass.
The final exam is worth 40 points. You need at least 18 points from the final exam to pass.
Line 42:
Line 47:
It will be a written exam, lasting 120 min. No books or notes will be allowed. The necessary formulas will be provided. The questions will be rather practical - you will be asked to solve (calculate) particular problems, similar to those during the lectures and labs.
It will be a written exam, lasting 120 min. No books or notes will be allowed. The necessary formulas will be provided. The questions will be rather practical - you will be asked to solve (calculate) particular problems, similar to those during the lectures and labs.
-
Exam dates:
+
**
Exam dates
** for Spring 2024
:
-
*
TBD (regular)
+
*
Presence exam: **Friday, May 31, 10:00**, KN:E-128
-
*
TBD
(re-take)
+
*
Presence exam: **Wednesday, June 5, 10:00**, KN:E-128
+
* Online exam for EuroTeQ students: **Thursday, June 6, 16:00**, BBB room
+
* Presence exam
(re-take)
: **Monday, June 17, 9:00**, KN:E-301
+
* Online exam for EuroTeQ students: TBA
courses/be5b33kui/start.txt
· Last modified: 2024/05/27 14:40 by
xposik