455852-HS2022-0-Data Science for Business Applications





Root number 455852
Semester HS2022
Type of course Lecture
Allocation to subject Business Administration
Type of exam Written exam
Title Data Science for Business Applications
Description As technology advances rapidly, the available data resources and the volume of data from which businesses can benefit have been substantially growing over time. In this regard, in the last decade, the demand for a new position, namely “data scientist” has become more prominent in many business firms.

This course aims at familiarizing students with what is being a data scientist in the business environment and how one can identify themselves as a data scientist. Students can attain the required knowledge on different aspects of data science and its implications for business. They will acquire a set of skills that will help them to develop themselves as data scientists, who can help business firms with data-driven decision-making.

The course will be taught online and includes two types of sessions:

Lectures: Students will be introduced to different concepts, methods, and applications. They will gain useful insights required for hands-on experiences in the workshop sessions.

Workshops: There will be sessions in which students will be introduced to scenarios, and they will be engaging in discussions on data, analytical approaches, and, most importantly, implementing the analysis using Python. No preliminary programming knowledge is required. Students will gain the necessary skills in the workshops. It is necessary that students use their personal notebooks for the workshop sessions.

This course will be held online.
Attendance and active participation of students in both lectures and workshops are highly recommended. Students also need to be willing to dedicate some time of their own to successfully accomplish the required tasks of this course.
ILIAS-Link (Learning resource for course) Registrations are transmitted from CTS to ILIAS (no admission in ILIAS possible). ILIAS
Link to another web site
Lecturers Prof. Dr. Hamid KhobziInstitute of Information Systems, Information Engineering 
ECTS 6
Recognition as optional course possible No
Grading 1 to 6
 
Dates Thursday 08:00-12:00 Weekly
Thursday 12/1/2023 10:15-11:45
Thursday 9/2/2023 10:15-11:45
 
Rooms
 
Students please consult the detailed view for complete information on dates, rooms and planned podcasts.