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Updated in [July 17th, 2023]
This course provides an overview of how to use Data Engineer to prepare financial data for machine learning and backtesting. Students will learn how to extract financial data using Data Builder, and how to structure data in such a way that seemingly mundane data can be transferred into useful information. Students will learn how to calculate returns in terms of values, percentages, differences and absolute moves (volatility), add time sequences to 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, and prepare features for machine learning (although not required for backtesting). No coding experience is required, although registered members of Crypto Wizards will have access to additional material.
Course Syllabus
Introduction - Getting Started
Transforming Features
TA - Technical Analysis
Conditions, Filters and ML Preparation
Summary - Putting It All Together
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