270299 VO Basics of Informatics for Chemistry and Biology (2024W)
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MIXED
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).
Details
max. 15 participants
Language: German
Lecturers
Classes (iCal) - next class is marked with N
- Friday 04.10. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 11.10. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 18.10. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 25.10. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 08.11. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 15.11. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 22.11. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 29.11. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 06.12. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 13.12. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- N Friday 10.01. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 17.01. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 24.01. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 31.01. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
Information
Aims, contents and method of the course
Assessment and permitted materials
Oral exam.
Due to the COVID situation exams will be held online via BigBlueButton.
Due to the COVID situation exams will be held online via BigBlueButton.
Minimum requirements and assessment criteria
Familiarity with basic computer science concepts.
Examination topics
All lecture content
Reading list
Slides and course materials will be made available via moodle.
Association in the course directory
BC-DAT I-1
Last modified: Th 03.10.2024 12:46
complexity analysis, with emphasis on algorithms relevant for Chemistry and
Biology such as string search and graph algorithms.
Concept of algorithm and data types. Complexity analysis of algorithms;
NP-completeness and computability; search methods and heuristics.
Course material: Lecture notes