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:

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.

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

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!