Machine Learning for Finance
21 hours – 3 days
- Basic familiarity with data manipulation (for instance, spreadsheet software) .
- General understanding of college-level math (probability, statistics, calculus).
- Familiarity with programming beneficial but not required.
Python is quickly gaining popularity in the financial world. Being a general-purpose programming language, it is suitable for quick integration of research prototypes into core trading programs and risk management systems.
- Introduction to Python. Data and control structures.
- Code vectorization. Numpy. Optimizing and benchmarking code.
- Data manipulation and visualization with pandas and matplotlib.
- Montecarlo simulations. Stochastic processes.
- Option valuation, trading strategies.
- Optional topics: Integration with Excel. Building a basic application.
- Developers, analysts and quants with experience in other tools (e.g. Matlab) that are considering a switch to Python for financial modelling.
- Portfolio Managers and other executives who want to have a high-level understanding of the potential of Python for Quantitative Finance.
Format of the course
- This is a hands-on course. Besides of the many exercises, the lecture part includes a substantial amount of live coding.
450 EUR/person + VAT.
Note: The course is designed to provide a broad overview. However, we can customize the course to cover your specific needs.