607.926 (23W) Methodology 3: Data Analytics
Overview
- Lecturer
- Course title german Methodology 3: Data Analytics
- Type Lecture - Course (continuous assessment course )
- Course model Attendance-based course
- Hours per Week 2.0
- ECTS credits 4.0
- Registrations 6 (30 max.)
- Organisational unit
- Language of instruction Englisch
- Course begins on 02.10.2023
- eLearning Go to Moodle course
Time and place
Course Information
Intended learning outcomes
Introduction to data analytics.
Teaching methodology
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/)
Course content
- Motivation, Data Collection and Preparation
- Data Visualization
- Association Rule Learning
- Cluster Analysis
- Regression Models
- Heuristic Methods
- Artificial Intelligence and Machine Learning
Prior knowledge expected
Sufficient prior knowledge in statistics as covered by Methodology II: Statistics.
Literature
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.
Examination information
Examination methodology
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.
Examination topic(s)
The exam is based on the actual contents discussed in the lecture.
Assessment criteria / Standards of assessment for examinations
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.
Grading scheme
Grade / Grade grading schemePosition in the curriculum
- Bachelor's degree programme Information Management
(SKZ: 522, Version: 17W.1)
-
Subject: Grundlagen des Informationsmanagements und Forschungsmethodik
(Compulsory subject)
-
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)
-
Subject: Grundlagen des Informationsmanagements und Forschungsmethodik
(Compulsory subject)
- Bachelor's degree programme Management Information Systems
(SKZ: 522, Version: 20W.2)
-
Subject: Grundlagen des Informationsmanagement und Forschungsmethodik
(Compulsory subject)
-
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)
-
Subject: Grundlagen des Informationsmanagement und Forschungsmethodik
(Compulsory subject)
- Bachelor's degree programme International Business and Economics
(SKZ: 516, Version: 19W.1)
-
Subject: Methodology in Business and Economics Research
(Compulsory subject)
-
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)
-
Subject: Methodology in Business and Economics Research
(Compulsory subject)
Equivalent courses for counting the examination attempts
- Wintersemester 2024/25
-
Wintersemester 2023/24
- 607.916 VC Methodology 3: Data Analytics (2.0h / 4.0ECTS)
- Sommersemester 2023
- Sommersemester 2022
- Sommersemester 2021