Financial Data Analytics
| Course number (Stud.IP): | 39901 (lecture) + 39902 (tutorial) |
| Examination number: | 221831 |
| Module: | DTBS: Major Management / Wahlpflichtbereich BAE: Schwerpunkt AFT BWI: Wahlpflichtmodule |
| Hours per week per semester: | 4 (lecture + tutorial) |
| Duration of the module: | 1 semester |
| Cycle: | Every semester (during summer semester tutorial only) |
| Expected achievement: | Exam: 40%
Project in presence: 60% |
| ECTS: | 5 |
Recommended entry requirements
Mathematcis and statistics; it would be advantageous to take the course "Data Analysis and Digital Reporting with Python“ (in the same semester).
Possibilty to retake exam
If you have failed the exam, you can retake it corresponding to § 6 of your course and examination regulations.
- Basics of data modelling
- Supervised and unsupervised learning
- Introduction in Neural Networks
- Underfitting, overfitting and validation
- Text handling in systematic data analysis
- Prediction, clustering and analysis of systematic relationships based on the principles of economics
Recommended literature:
- An Introduction to Statistical Learning (2013) – James, G., Witten, D., Hastie, T., Tibshirani, R.; Springer
- Hands-On Machine Learning with Scikit-Learn, Keras & Tensorflow (2017) – Geron, A.; Wiley
Students understand the function of data modelling, based on this knowledge they are able to learn new models and are also able to choose appropriate models for the particular issue. You will learn relevant aspects for professional practice in analysis of financial data by using the methods learned in this course.
Teaching form
- Interactive lecture, including digital supporting documents and learning videos.
- Interactive tutorials, including data analysis made by your own.
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