Data Engineer: Prepare Financial Data for ML and Backtesting

After learning how to extract financial data using Data Builder, you will naturally be wondering how to make use of all the standard data you have pulled. In this course, you will learn how to structure data in such a way that seemingly mundane data can be transferred into useful information that can give you an edge in the financial markets.

Using Data Engineer, you will be able to:

• Calculate returns in terms of values, percentages, differences, and absolute moves (volatility)
• Add time sequences to your data for predictions in machine learning
• Add correlation and co-integration information comparing any columns/features for any assets
• Add technical indicators
• Add conditions for making predictions about the future
• Add filters for removing unnecessary data
• Prepare your features for machine learning (although not required for backtesting

You will be able to do all of this without writing a single line of code. However, you will need to be a registered member of Crypto Wizards to take advantage of this material as this course was built to teach users (as requested) how to use the platform. If you are not a registered member, you can still take valuable principles away from this course and perhaps code this yourself using Python or another data science-related approach.

See you in class.