Download Udemy – MQL5 Beginner: Algorithmic trading with MQL5 (New 2021) 2022-3

MQL5 Beginner: Algorithmic trading with MQL5 (New 2021)

Description

MQL5 Beginner: Algorithmic trading with MQL5 (New 2021), is the name of the MQL5 algorithmic trading training course, which will comprehensively guide you through the basics and principles you need to be proficient in this language, algorithmic trading is a trading method that uses automatic pre-programmed trading instructions to execute trades, and MQL5 is one of the programming languages ​​used to set those trading instructions, and variables such as time, price, and volume. Algorithmic trading with MQL5 has the advantages of speed, impersonality, and the use of computing resources of computers over human traders.

Topics covered in this course include: storing data in MQL5 variables, MQL5 data types, operators and operations in MQL5, conditional operators in MQL5, loops in MQL5, functions in MQL5, object-oriented programming in MQL5 with classes , and the MQL5 projects section, in which some indicators and expert advisors or trading robots have been created to help implement algorithmic trading.

Things you will learn in this course:

  • Basics and basics of MQL5
  • How to read and understand MQL5 code
  • How to create and understand custom indicators
  • How to create and understand expert advisors

This course is suitable for people who:

Anyone interested in learning the MQL5 language.

Specifications of MQL5 Beginner course: Algorithmic trading with MQL5 (New 2021):

Course topics:

Course prerequisites:

No programming experience needed, you will learn all the basics you need in this MQL5 course.

Course images:

MQL5 Beginner: Algorithmic trading with MQL5 (New 2021)

Course introduction video:

Installation guide:

After Extract, view with your desired Player.

English subtitle

Quality: 720p

download link

1: Download part 1 – 2 GB

2: Download part 2 – 2 GB

3: Download part 3 – 2 GB

4: Download part 4 – 539 MB

Password file(s): www.downloadly.ir

Size

6.52 GB

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