MENUMENU
MENUMENU

Data Science and Analytics (DLMBDSA)

Modulbezeichnung: Data Science and Analytics

Modulnummer:

DLMBDSA

Semester:

--

Dauer:

Minimum 1 Semester

Modultyp:

Wahlpflicht

Regulär angeboten im:

Workload: 300 h

ECTS Punkte : 10

Zugangsvoraussetzungen:

None

Unterrichtssprache:

Englisch

Kurse im Modul:

Workload:

Self-study: 200 h
Self-examination: 50 h
Tutorials: 50 h

Kurskoordinatoren/Tutoren::

Please see the current list of tutors on the Learning Management System.

Modulverantwortliche(r):

Prof. Dr. Markus C. Hemmer

Bezüge zu anderen Programmen:

  • Master of Business Administration

Bezüge zu anderen Modulen im Programm:

  • Corporate Finance

Qualifikations- und Lernziele des Moduls :

Data Science:
Upon successful completion, students are able

  • to understand the techniques to store data.
  • to understand how data are pre-processed to prepare them for analysis.
  • to develop typologies for data and ontologies for knowledge representation.
  • to decide for appropriate mathematical algorithms to utilize data analysis for a given task.
  • to understand the value, applicability, and limitations of artificial intelligence for data analysis.

Analytical Software and Frameworks:
Upon successful completion, students are able

  • to understand how cloud computing and distributed computing support the field of data analytics.
  • to understand in-memory database technologies for real-time analytics.
  • to apply advanced statistics and machine learning solutions to solve data analysis problems.
  • to compare the capabilities and limitations of the presented software solutions.
  • to assist in decision-making for the most appropriate solution for a given business case.

Lehrinhalt des Moduls:

Data Science:

  • Introduction to Data Science
  • Data Storage
  • Pre-processing of Data
  • Processing of Data
  • Selected Mathematical Techniques
  • Selected Artificial Intelligence Techniques

Analytical Software and Frameworks:

  • Introduction
  • Statistical Modelling
  • Machine Learning
  • Cloud Computing Platforms
  • Distributed Computing
  • Database Technologies

Lehrmethoden:

See the contributing course outlines

Literatur:

See the contributing course outlines

Anteil der Modulnote an der Gesamtabschlussnote des Programms :

--

Prüfungszulassungsvoraussetzung:

Abschlussprüfungen:

See the contributing course outlines

DLMBBD01:
Exam, 90 min. (50 %)
DLMBBD02:
Written Assessment: Written Assignment (50 %)