Lazy Trading Part 7: Developing Self Learning Trading Robot

Learn to assemble Smart Learning Algorithms. Predict future price change based on financial data patterns

About Course

About this Course: Developing Self Learning Trading Robot

The seventh part of this series will cover an attempt to develop Self-learning Trading System:

  • Learn to use MQL4 to gather financial asset data
  • Learn to use R Statistical Software to prepare data for Machine Learning Problem
  • Use H2O Machine Learning Platform to train Deep Learning Models
  • Back-test potential trading strategy using Deep Learning Models
  • Use Model and New Data to generate predictions
  • Productionise your model in R and use it's output in MQL4 
  • Get Trading robot which does not require periodic optimizations

Important: Course features development path of the automating conceptually self-sufficient trading system. Some lectures of the course (as explicitly stated in section 5) will contain coding mistakes that would be found and corrected during the course development. Author of the course believes that coding mistakes are the part of the learning process and provides Lessons Learned on how to avoid them


About the Lazy Trading Courses:

This series of courses is designed to to combine fascinating experience of Algorithmic Trading and at the same time to learn Computer and Data Science! Particular focus is made on building foundation of Decision Support System that can help to automate a lot of boring processes related to Trading.

This project is containing several short courses focused to help you managing your Automated Trading Systems:

  1. Set up your Home Trading Environment
  2. Set up your Trading Strategy Robot
  3. Set up your automated Trading Journal
  4. Statistical Automated Trading Control
  5. Reading News and Sentiment Analysis
  6. Using Artificial Intelligence to detect market status
  7. Building an AI trading system

IMPORTANT: all courses will be short focusing to one specific topic with very short theoretical explanations. These courses will help to focus on developing strategies by automating boring but important processes for a trader.

What will you learn apart of trading:

While completing these courses you will learn much more rather than just trading by using provided examples:

  • Learn and practice to use Decision Support System
  • Be organized and systematic using Version Control and Automated Statistical Analysis
  • Learn using R to read, manipulate data and perform Machine Learning including Deep Learning
  • Learn and practice Data Visualization
  • Learn sentiment analysis and web scrapping
  • Learn Shiny to deploy any data project in hours
  • Get productivity hacks
  • Learn to automate your tasks and scheduling them
  • Get expandable examples of MQL4 and R code

What these courses are not:

  • These courses will not teach and explain specific programming concepts in details
  • These courses are not meant to teach you basics of Data Science or Trading
  • There is no guarantee on bug free programming


Trading is a risk. This course must not be intended as a financial advice or service. Past results are not guaranteed for the future.

Who this course is for:
  • Anyone who want to be more productive
  • Anyone who want to learn Data Science using Algorithmic Trading
  • Anyone who want to try Algorithmic Trading but have little time
  • Anyone willing to learn Deep Learning and understand how to apply it to make predictions