607.926 (23W) Methodology 3: Data Analytics
Überblick
- Lehrende/r
- LV-Titel englisch Methodology 3: Data Analytics
- LV-Art Vorlesung-Kurs (prüfungsimmanente LV )
- LV-Modell Präsenzlehrveranstaltung
- Semesterstunde/n 2.0
- ECTS-Anrechnungspunkte 4.0
- Anmeldungen 6 (30 max.)
- Organisationseinheit
- Unterrichtssprache Englisch
- LV-Beginn 02.10.2023
- eLearning zum Moodle-Kurs
Zeit und Ort
LV-Beschreibung
Intendierte Lernergebnisse
Introduction to data analytics.
Lehrmethodik
There are two parts - lectures and practice sessions. Practice sessions require mandatory attendance. See the description in Moodle for details.
607.916: Practice sessions 13:00 - 14:30
607.926: Practice sessions 14:45 - 16:15
We will use statistical software R (R Studio). It would be helpful to install it in advance: https://www.r-project.org/. (R Studio: https://posit.co/)
Inhalt/e
- Motivation, Data Collection and Preparation
- Data Visualization
- Association Rule Learning
- Cluster Analysis
- Regression Models
- Heuristic Methods
- Artificial Intelligence and Machine Learning
Erwartete Vorkenntnisse
Sufficient prior knowledge in statistics as covered by Methodology II: Statistics.
Literatur
A significant part of the lecture is covered by “Data Science for Business: What you need to know about data mining and data-analytic thinking” by F. Provost & T. Fawcett and by "Data mining: concepts and techniques" by J. Han & M. Kamber.
Prüfungsinformationen
Prüfungsmethode/n
Lectures: multiple choice online exam - 60 minutes time for 10 questions with 4 true/false statements each.
Practice sessions: exercises; active participation in the discussion.
Please note that both the successful completion of the practice sessions and the positive result from the multiple-choice exam related to the lectures are necessary in order to complete the Data Analytics VC successfully. If only one of the two parts is not completed successfully Data Analytics VC needs to be repeated altogether.
See description in Moodle for details, especially regarding the practice sessions.
Prüfungsinhalt/e
The exam is based on the actual contents discussed in the lecture.
Beurteilungskriterien/-maßstäbe
Lectures: Of the possible maximal 40 points you must reach at least 28 points to get a positive grade.
Practice sessions: Based on the checklists and presentations of exercises you must reach at least 60% = 15 points of the possible maximal 25 points to get a positive grade.
Lectures contribute 2/3 and practice sessions 1/3 to the total grade.
Please note that both the successful completion of the practice sessions and the positive result from the multiple-choice exam related to the lectures are necessary in order to complete the Data Analytics VC successfully.
Beurteilungsschema
Note BenotungsschemaPosition im Curriculum
- Bachelorstudium Informationsmanagement
(SKZ: 522, Version: 17W.1)
-
Fach: Grundlagen des Informationsmanagements und Forschungsmethodik
(Pflichtfach)
-
3.3 Methoden der empirischen Sozialforschung (
1.0h VO / 2.0 ECTS)
- 607.926 Methodology 3: Data Analytics (2.0h VC / 2.0 ECTS) Absolvierung im 3. Semester empfohlen
-
3.3 Methoden der empirischen Sozialforschung (
1.0h VO / 2.0 ECTS)
-
Fach: Grundlagen des Informationsmanagements und Forschungsmethodik
(Pflichtfach)
- Bachelorstudium Wirtschaftsinformatik
(SKZ: 522, Version: 20W.2)
-
Fach: Grundlagen des Informationsmanagement und Forschungsmethodik
(Pflichtfach)
-
3.2 Methoden der empirischen Sozialforschung (
0.0h VO, VI, VC / 4.0 ECTS)
- 607.926 Methodology 3: Data Analytics (2.0h VC / 4.0 ECTS) Absolvierung im 3. Semester empfohlen
-
3.2 Methoden der empirischen Sozialforschung (
0.0h VO, VI, VC / 4.0 ECTS)
-
Fach: Grundlagen des Informationsmanagement und Forschungsmethodik
(Pflichtfach)
- Bachelorstudium International Business and Economics
(SKZ: 516, Version: 19W.1)
-
Fach: Methodology in Business and Economics Research
(Pflichtfach)
-
7.3 Methodology 3 (
0.0h VO, VI, VC, KS / 4.0 ECTS)
- 607.926 Methodology 3: Data Analytics (2.0h VC / 4.0 ECTS) Absolvierung im 1., 2., 3. Semester empfohlen
-
7.3 Methodology 3 (
0.0h VO, VI, VC, KS / 4.0 ECTS)
-
Fach: Methodology in Business and Economics Research
(Pflichtfach)
Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung
-
Wintersemester 2023/24
- 607.916 VC Methodology 3: Data Analytics (2.0h / 4.0ECTS)
- Sommersemester 2023
- Sommersemester 2022
- Sommersemester 2021