|Lecturer:||Prof. Dr. Stefan Mayer|
|Course description:|| |
|Recommended for this semester or higher:||1|
|Course can be taken as part of following programs/modules:|| |
Economics and Finance
Data Science in Business and Economics
|Prerequisite for:|| |
|Course Type:||Lecture (2 weekly lecture hours)|
Tuesday, November 3, 2020, from 4pm c.t. – 6pm
Limited to 45 participants. Registration open for all (no first-come, first-served): Registration will open on Monday, October 1, 2020 on ILIAS - end of registration time: Monday, October 19, 2020 (23:55pm). If the number of applications (limited to 45 participants) exceeds the number of places available, we unfortunately will not be able to accept all of the applicants. In this case, a random selection will be made from all the applications received. Preferred access for master students from the Data Science in Business and Economics program.
|Method of Assessment:|| |
Written exam (90 Minutes), or oral examination, or assignments or presentation or online assessment (90 Minutes)
|Content:||The course is an introduction to data science using Python. After a general introduction to Python, the following topics are covered: Data preparation, management, transformation, and cleaning; data visualization; machine learning.|
Students who successfully complete the course know the most important basics of working with Python and are able to perform the complete process of data preparation, visualization and analysis with Python and apply their knowledge to real data sets.
VanderPlas, J. (2016). Python Data Science Handbook. O’Reilly Media. jakevdp.github.io/PythonDataScienceHandbook/