040164 UE Python for Finance I (MA) (2023W)
Continuous assessment of course work
Labels
ON-SITE
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 11.09.2023 09:00 to Fr 22.09.2023 12:00
- Registration is open from Tu 26.09.2023 09:00 to We 27.09.2023 12:00
- Deregistration possible until Fr 20.10.2023 23:59
Details
max. 35 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Monday
02.10.
13:15 - 14:45
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday
09.10.
13:15 - 14:45
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday
16.10.
13:15 - 14:45
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday
23.10.
13:15 - 14:45
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday
30.10.
13:15 - 14:45
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday
06.11.
13:15 - 14:45
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday
13.11.
13:15 - 14:45
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday
20.11.
13:15 - 14:45
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday
27.11.
13:15 - 14:45
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday
04.12.
13:15 - 14:45
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday
11.12.
13:15 - 14:45
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday
08.01.
13:15 - 14:45
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday
15.01.
13:15 - 14:45
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday
22.01.
13:15 - 14:45
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday
29.01.
13:15 - 14:45
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Information
Aims, contents and method of the course
Assessment and permitted materials
The grade will be based on homework exercises that participants are expected to present in class, active class participation including in-class exercises, and a final exam. The final exam will take place on January, 29.
Minimum requirements and assessment criteria
40% homework exercises
20% in-class exercises and active class participation
40% final examMinimum requirement for a positive grade: a total of 50%.
20% in-class exercises and active class participation
40% final examMinimum requirement for a positive grade: a total of 50%.
Examination topics
All material covered in class.
Reading list
Main reference:Sheppard, Kevin. Introduction to Python for Econometrics, Statistics and Data Analysis, 2021. https://www.kevinsheppard.com/files/teaching/python/notes/python_introduction_2021.pdfMcKenney, Wes. Python for Data Analysis, 2nd edition, 2017. O'Reilly Media.Official Python documentation and tutorials: https://docs.python.org/3/tutorial/index.html
Association in the course directory
Last modified: Fr 29.09.2023 08:06
2. Numerical Computing with NumPy
3. Data Analysis with pandas
4. Regression Analysis with statsmodels and linearmodelsFurthermore, data visualization with matplotlib will be part of all chapters.