Data Engineer: Prepare Financial Data for ML and Backtesting
Data Engineer: Prepare Financial Data for ML and Backtesting, available at Free, has an average rating of 4.5, with 16 lectures, based on 74 reviews, and has 5786 subscribers.
You will learn about Extract meaningful features out of mundane price and volume data for Machine Learning and Backtesting Join data tables Add time steps to your data Automatically calculate correlation and cointegration Add technical indicators within seconds Add conditional features without needing excel Filter your data table Prepare your data for Machine Learning This course is ideal for individuals who are Retail traders and retail quants looking to gain an edge in the financial and crypto markets It is particularly useful for Retail traders and retail quants looking to gain an edge in the financial and crypto markets.
Enroll now: Data Engineer: Prepare Financial Data for ML and Backtesting
Summary
Title: Data Engineer: Prepare Financial Data for ML and Backtesting
Price: Free
Average Rating: 4.5
Number of Lectures: 16
Number of Published Lectures: 16
Number of Curriculum Items: 16
Number of Published Curriculum Objects: 16
Original Price: Free
Quality Status: approved
Status: Live
What You Will Learn
- Extract meaningful features out of mundane price and volume data for Machine Learning and Backtesting
- Join data tables
- Add time steps to your data
- Automatically calculate correlation and cointegration
- Add technical indicators within seconds
- Add conditional features without needing excel
- Filter your data table
- Prepare your data for Machine Learning
Who Should Attend
- Retail traders and retail quants looking to gain an edge in the financial and crypto markets
Target Audiences
- Retail traders and retail quants looking to gain an edge in the financial and crypto markets
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:
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Calculate returns in terms of values, percentages, differences and absolute moves (volatility)
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Add time sequences to your data for predictions in machine learning
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Add correlation and co-integration information comparing any columns/features for any assets
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Add technical indicators
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Add conditions for making predictions about the future
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Add filters for removing unnecessary data
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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.
Course Curriculum
Chapter 1: Introduction – Getting Started
Lecture 1: Introduction – The Power of Data Engineering
Lecture 2: Data Extraction – Downloading and Viewing Data
Lecture 3: Table Stats – Data Statistical Overview
Chapter 2: Transforming Features
Lecture 1: Transform Features – Part 1 (Basics)
Lecture 2: Transform Features – Part 2 (Returns)
Lecture 3: Transform Features – Part 3 (Time-steps)
Lecture 4: Transform Features – Part 4 (Joining Data)
Lecture 5: Transform Features – Part 5 (Correlation and Co-integration)
Lecture 6: Transform Features – Part 6 (Drop NA)
Chapter 3: TA – Technical Analysis
Lecture 1: TA – Part 1
Lecture 2: TA – Part 2
Chapter 4: Conditions, Filters and ML Preparation
Lecture 1: Conditional Signals and Outcomes
Lecture 2: Filtering Data
Lecture 3: ML Prep – Preparation for Machine Learning
Chapter 5: Summary – Putting It All Together
Lecture 1: End to End Walkthrough
Lecture 2: Congratulations and Closing Comments
Instructors
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Shaun McDonogh
Lead Analyst and Full Stack (Python and React) Developer
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 1 votes
- 3 stars: 4 votes
- 4 stars: 16 votes
- 5 stars: 52 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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