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.

Course Outline

  • 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.

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