Prerequisites

This is not a beginner course. It assumes you can already program and analyze data, and it teaches you how to apply those skills to financial markets. Trading experience is not required.

For general expectations about zoomcamp time commitment, see Before You Start.

Required skills

You need these basics:

  • Python programming at an intermediate level. All course code is Python, and every homework requires writing code.
  • Data analysis with pandas. The course uses time series operations that go beyond the basics.
  • An experimental and creative mindset. There is no single path to a good model or a profitable strategy, so you need to be comfortable forming a hypothesis and testing it quickly.
  • Interest in financial markets and investing.

The coding is not complicated: no object-oriented programming and no advanced data structures. If you have a few years of experience in any language, you will manage.

You do not need

You do not need these before starting:

  • Trading experience. Most participants in previous cohorts had never placed a trade.
  • A brokerage account. You can complete the whole course without ever placing a trade, though opening an account makes the material sink in faster.
  • A finance or economics background. Economic concepts are explained as they come up.
  • Deep statistics. Some distributions and statistical models appear, but without deriving what happens under the hood.
  • Time series experience. It helps, but the Predicting Financial Time-Series workshop covers what you need.

Time commitment

Plan for 10 to 15 hours per week. In previous cohorts participants reported roughly 4 hours on lectures and 5 or more hours on homework per module, with the first modules being the most intense.

The project takes around 20 hours for most people. Taking this course in parallel with another zoomcamp is possible but demanding.

If you are a beginner

You can still finish, but expect it to cost you much more time. One participant in the 2024 cohort came from a non-technical background and spent about 100 hours on the project, compared to about 20 hours for most others.

If you want to prepare, take a short course on Python and pandas first, and work through the previous cohort’s materials in the GitHub repository to check whether the level suits you.