Modulcode: | infDaSci-01a |
Englische Bezeichnung: | Data Science |
Modulverantwortliche(r): | Prof. Dr. Matthias Renz |
Turnus: | jedes Jahr im WS (WS21/22 WS22/23 WS23/24 WS24/25) |
Präsenzzeiten: | 3V 1Ü |
ECTS: | 5 |
Workload: | 45 h lectures, 15 h exercises, 90 h self studies |
Dauer: | ein Semester |
Modulkategorien: | BSc-Inf-A (BSc Inf (21)) BSc-WInf-WP-WInf (BSc WInf (21)) WI (BSc Inf (15)) 2F-MEd-Inf-WP (MEd-Hdl Inf (21)) 2F-MA-Inf-WP (2F-MA Inf (21)) MSc-WInf-WP-WInf (MSc WInf (21)) WI (MSc Inf (15)) WI (MSc WInf (15)) NF (Inf. als NF) INF-Math (Inf. als NF) INF-VWL (Inf. als NF) Arch-NFInf21 (Inf. als NF) EcoQuantFin (Export) |
Lehrsprache: | Englisch |
Voraussetzungen: | Inf-Math-A Inf-Math-B |
The lecture is intended to convey the basics for the presentation, processing and use of data to gain (new) knowledge and derive recommendations for action. The most important aspects of the life cycle of data are addressed, starting with data formats and structures, which play an important role in the collection and management of the data, through methods for processing and using the data, through to the representation and communication of the data knowledge and knowledge gained.
The students
Written exam
Prerequisits for the exam: home work
In the lecture, the material is conveyed in different forms (blackboard, projector), which are selected depending on the respective content. For the most part of the lecture there are slides, which are made available together with other documents on the website of the event. Theoretical and practical tasks related to the subject matter taught in the lecture are dealt with in the exercises. The solutions are discussed.
Students who did not pass this module as a mandatory module in their Bachelor, can choose this module as an elective module within their Bachelor or Master studies.
The lecture will start in winter term 21/22.