052414 VU Concepts and Models of Knowledge Engineering (2018W)
Continuous assessment of course work
Labels
Summary
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Sa 08.09.2018 09:00 to Su 23.09.2018 23:59
- Deregistration possible until Su 14.10.2018 23:59
Registration information is available for each group.
Groups
Group 1
max. 25 participants
Language: English
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
Wednesday
03.10.
08:00 - 09:30
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
03.10.
15:00 - 16:30
Seminarraum 7, Währinger Straße 29 1.OG
Wednesday
21.11.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
22.11.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
28.11.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
29.11.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
05.12.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
06.12.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Monday
10.12.
08:00 - 09:30
Hörsaal 1, Währinger Straße 29 1.UG
Wednesday
12.12.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
09.01.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
10.01.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
16.01.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
17.01.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
23.01.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
24.01.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Monday
28.01.
15:00 - 16:30
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Group 2
max. 25 participants
Language: English
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
Wednesday
03.10.
08:00 - 09:30
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
03.10.
15:00 - 16:30
Seminarraum 7, Währinger Straße 29 1.OG
Wednesday
21.11.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
22.11.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
28.11.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
29.11.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
05.12.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
06.12.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Monday
10.12.
08:00 - 09:30
Hörsaal 1, Währinger Straße 29 1.UG
Wednesday
12.12.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
09.01.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
10.01.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
16.01.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
17.01.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
23.01.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
24.01.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Monday
28.01.
15:00 - 16:30
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Information
Aims, contents and method of the course
In this lecture, the goal is to gain expertise on the state of the art in knowledge engineering. Therefore, students explore the relevant theory and reinforce their knowledge in exercises.
Assessment and permitted materials
Two exams have to be written, one in the middle and one at the end of the semester. The exams will contain theory questions and applied problems, based on the lectures, a script with lecture content, and exercises. During the test, no unauthorized materials are allowed and all electronic devices have to be turned off.In detail, the grade is constituted by:
* 1st exam 40%
* 2nd exam 40%
* Exercises 20%Missing class more than three times results in a negative grade.
* 1st exam 40%
* 2nd exam 40%
* Exercises 20%Missing class more than three times results in a negative grade.
Minimum requirements and assessment criteria
For a positive evaluation of the course, more or equal to 50% of requirements have to be fulfilled. The grading scale is defined as follows: >50% - 62,5%: Genügend; >62,5% - 75%: Befriedigend; >75% - 87,5%: Gut; >87,5%: Sehr Gut
Examination topics
Neural Networks I
Machine Learning
Neural Networks II
Evolutionary Computation
Bayesian Scheme
Hidden Markov Models
Agent Systems
Constraint Satisfaction
Semantic Web
Machine Learning
Neural Networks II
Evolutionary Computation
Bayesian Scheme
Hidden Markov Models
Agent Systems
Constraint Satisfaction
Semantic Web
Reading list
Script with lecture content
Moodle courseDimitris Karagiannis, Rainer Telesko: Wissensmanagement: Konzepte der künstlichen Intelligenz und des Softcomputing
Stuart J. Russell, Peter Norvig: Artificial Intelligence - A Modern Approach
Moodle courseDimitris Karagiannis, Rainer Telesko: Wissensmanagement: Konzepte der künstlichen Intelligenz und des Softcomputing
Stuart J. Russell, Peter Norvig: Artificial Intelligence - A Modern Approach
Association in the course directory
Module: WI2 KE
Last modified: Mo 07.09.2020 15:30