040164 KU Python for Finance I (MA) (2020W)
Continuous assessment of course work
Labels
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 14.09.2020 09:00 to We 23.09.2020 12:00
- Registration is open from Mo 28.09.2020 09:00 to We 30.09.2020 12:00
- Deregistration possible until Sa 31.10.2020 12:00
Details
max. 35 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Monday 05.10. 13:15 - 14:45 Digital
- Monday 12.10. 13:15 - 14:45 Digital
- Monday 19.10. 13:15 - 14:45 Digital
- Monday 09.11. 13:15 - 14:45 Digital
- Monday 16.11. 13:15 - 14:45 Digital
- Monday 23.11. 13:15 - 14:45 Digital
- Monday 30.11. 13:15 - 14:45 Digital
- Monday 07.12. 13:15 - 14:45 Digital
- Monday 14.12. 13:15 - 14:45 Digital
- Monday 11.01. 13:15 - 14:45 Digital
- Monday 18.01. 13:15 - 14:45 Digital
- Monday 25.01. 13:15 - 14:45 Digital
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, and a final exam. The final exam will take place on Moodle on January, 25.The course will be taught via video conferencing.
Minimum requirements and assessment criteria
60% homework exercises
10% active class participation
30% final examMinimum requirement for a positive grade: a total of 50%.
10% active class participation
30% 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, 2019. https://www.kevinsheppard.com/files/teaching/python/notes/python_introduction_2019.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 12.05.2023 00:12
We will start with an introduction to programming and the basics of Python. Subsequently, the course will consist of an introduction to some of the Python packages most relevant for applications in Finance.
This course is of an applied nature, with the goal of enabling students to use Python to solve problems they may encounter in practice.Main Topics of the Course:1. Python and Programming Basics
2. Numerical Computing with NumPy
3. Data Analysis with pandasOther topics: data Visualization with matplotlib and regression analysis with statsmodels and linearmodels.