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Root number
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455852 |
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Semester
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HS2019 |
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Type of course
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Lecture |
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Allocation to subject
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Business Administration |
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Type of exam
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Written exam |
| Title |
Data Science for Business Applications |
| Description |
As technology advances rapidly, the available data resources and the volume of data from which business 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 a data scientist, who can help business firms with data-driven decision making.
The course 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 with 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 bring their personal notebook to the workshop sessions.
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. |
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ILIAS-Link (Learning resource for course)
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Registrations are transmitted from CTS to ILIAS (no admission in ILIAS possible).
ILIAS
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Link to another web site
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| Lecturers |
Prof. Dr.
Hamid Khobzi, Institute of Information Systems, Information Engineering
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ECTS
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6 |
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Recognition as optional course possible
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No |
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Grading
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1 to 6 |
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| Dates |
Tuesday 14:00-16:00 Weekly
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Wednesday 14:00-15:45 Weekly
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Thursday 9/1/2020 09:00-10:15
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Tuesday 11/2/2020 13:00-14:15
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| Rooms |
Hörsaal 2 002, Engehalde, E8
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Seminarraum 105, Hauptgebäude H4
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| External rooms |
Enge 8, HR 001
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| Students please consult the detailed view for complete information on dates, rooms and planned podcasts. |
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