270299 VO Basics of Informatics for Chemistry and Biology (2022W)
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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
Examination dates
Lecturers
Classes (iCal) - next class is marked with N
Erster Termin am 14.10!
- Friday 07.10. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 14.10. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 21.10. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 28.10. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 04.11. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 11.11. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 18.11. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 25.11. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 02.12. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 09.12. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 16.12. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 13.01. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 20.01. 11:30 - 13:00 Seminarraum 11, Währinger Straße 29 2.OG
- Friday 27.01. 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, IMA I-1
Last modified: Tu 18.04.2023 09:50
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