About the Lazy Trading Courses:
This series of courses is designed totocombine fascinating experience ofAlgorithmic Trading and at the same time tolearn Computer andData Science! Particular focus is made on buildingDecision Support System that can help to automate a lot of boring processes related to Trading and also learn Data Science. Several algorithms will be built by performing basic data cycle 'data input-data manipulation - analysis -output'. Provided examples throughout all 7 courses will show how to build very comprehensive system capable to automatically evolve without much manual input.

Inspired by:
“it is insane to expect that one system to work for all market types” // -Van K. Tharp

“Luck is what happens when preparation meets opportunity” // -Seneca (Roman philosopher)

About this Course:Use Artificial Intelligence in Trading
This course will cover usage of Deep Learning Classification Model to classify Market Status of Financial Assets using Deep Learning:

• Learn to use R and h2oMachine Learning platform to train Supervised Deep Learning Classification Models

• Easily gather and write Financial Asset Data withData Writer Robot

• Manipulate data andlearn to build ClassificationDeep Learning Models

  • Use random neural network structures

  • Functions with examples in Rpackage

• Generate Market Type classification output for Trading Systems

• Get Trading robot capable to considerMarket Status information in your Strategies

This project iscontaining several short coursesfocused 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 automatedTrading Journal

4. Statistical Automated Trading Control

5. Reading News and Sentiment Analysis

6. Using Artificial Intelligence to detect market status

7. Building anAI trading system

Update:dedicated R package 'lazytrade' was created to facilitate code sharing among different courses

IMPORTANT:all courses will have a 'quick to deploy' sections as well as sections containing theoretical explanations.

What will you learn apart of trading:

While completing thesecourses 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 practiceData Visualization

• Learn sentiment analysis and web scrapping

• Learn Shiny to deploy any data project in hours

• Get productivity hacks

• Learn to automate your tasksand 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 basics of Data Science or Trading

• There is no guarantee onbug free programming

Disclaimer:

Trading is a risk. This course must not be intended as a financial advice or service. Past results are not guaranteed for the future. Significant time investment may be required to reproduce proposed methods and concepts