Current Topics in Data Science: Real-world financial market problems
| Duration | 1 semester |
|---|---|
| State of the module | Elective module |
| ECTS | 5 |
| Hours of compulsory in credit hours | 4 |
| Learning outcome/ competencies | The module focuses on the application of business analytics and data science techniques to real-world financial market problems. Students apply Python-based analytical methods to financial data in order to support market analysis, valuation, risk assessment, and investment decision-making. The previous knowledge of Python is not required. A central component of the course is the hands-on use of the Bloomberg Terminal for data retrieval, financial analysis, and professional-grade market intelligence. Students learn how to combine programming-based analytics with industry-standard financial platforms, reflecting current practices in financial institutions, consulting, and asset management. The previous knowledge of Bloomberg is not required. The course includes one on-site visit to the Bloomberg office in Berlin and one guest seminar delivered by a Bloomberg representative on campus, providing direct exposure to professional workflows and applied use cases. The course does not require previous knowledge of economics and finance. Students who are not familiar with economics will have an opportunity to take an eight-hour economics course (BMC) in the Bloomberg lab. They will receive a certificate for completing the course and decent background to complete the module successfully. Module Content
|
| Necessary requirements | None |
| Recommended requirements | None
|
| Method of examination (applicable are §§ 9-14 RStPO) | 3 practical assignments over the course of the semester:
|