Lazy Trading Part 1: Set up Home Computer on Windows 10




Lazy Trading Part 1: Set up Home Computer on Windows 10

"Luck is a preparation to Opportunity" -- Seneca

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 Decision 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.

About this Course: Set up your Trading Environment

This course will cover setting up personal Home Trading Environment using Windows 10 Operating System. At the end of this course we will have a Trading Environment installed and active on the Home Computer. This trading environment will be a basis of a modular system which will be completed during the whole series of courses. We will cover the following topics:

  • Choosing a hardware (Windows PC)

  • Learning about basic administrative tools in Windows 10

  • Install and prepare needed software including Meta Trader 4 Platform

  • Establish Version Control Tools for Trading Strategies and tools

  • Outline the Bigger Strategy that aims to automate decisions of the Trader

  • Set up Development, Test and Production Trading Terminals

  • Establish Decision Support System using R statistical software and package 'lazytrade'

  • Making Trading Environment more robust to external factors

"What is that ONE thing very special about this course?"

-- Setting up the computer to be ready 24/7!

This project is containing several 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 have a 'quick to deploy' sections as well as sections containing theoretical explanations.

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 basics of Data Science or Trading

  • There is no guarantee on bug 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

Learn Computer and Data Science through Algorithmic Trading, set up Trading Environment on Windows

Url: View Details

What you will learn
  • Computer Management Tools and Settings
  • Using version control to track changes
  • Setup Trading Terminals

Rating: 4.25

Level: All Levels

Duration: 6.5 hours

Instructor: Vladimir Zhbanko


Courses By:   0-9  A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z 

About US

The display of third-party trademarks and trade names on this site does not necessarily indicate any affiliation or endorsement of hugecourses.com.


© 2021 hugecourses.com. All rights reserved.
View Sitemap