Data Structures and Algorithmic Trading: Machine Learning

2h 20m 32s
English
Paid

Data Structures and Algorithmic trading is a method of executing orders using automated pre-programmed trading instructions over time. They were developed so that traders do not need to constantly watch a stock and repeatedly send those slices out manually. Algorithmic trading is not an attempt to make a trading profit. It is simply a way to minimize the cost, market impact and risk in execution of an order, but if you can’t use this incredible tool, you might miss the right entry or exit spots that other traders will gladly take.

Read more about the course

What if you could change that?

My complete Algorithmic Trading course will show you the exact techniques and strategies you need to succeed in the financial markets, master trading, build a forex robot and learn machine learning.

For less than a movie ticket, you will get over 4 hours of video lectures and the freedom to ask me any questions regarding the course as you go through it. :)

What Is In This Course?

Your Trading Will Never Be The Same.

Except if you’re already an excellent trader, know the importance of sorting, use array rotation, read technical analysis, finding shortest path in a graph and know AVL treesyou are going to lose more opportunities to code faster and more effectively.

In This Data Structures & Algorithmic Trading Training, You'll Learn:

  • Learn Algorithmic Thinking
  • Computational Problem Solving Using Algorithms
  • Algorithmic Design Process
  • Importance of Sorting
  • Array Rotation
  • Insertion Sort
  • Merge & Heap Sort
  • Greedy Algorithms
  • Topological Sorting
  • Breadth & Depth First Traversal
  • Hashing
  • Open Addressing
  • Finding Shortest Path in a graph
  • AVL trees
  • Computational Complexity and Machine Learning

Is This For You?

  • Do you want to do algorithmic trading with machine learning?
  • Are you afraid of not creating a good Forex robot and earn money through trading?
  • Do you think you will feel proud making successful trades with your Forex robots?

Then this course will definitely help you.

This course is essential to all Forex trader, stockbroker, entrepreneur, systematic traders, short term traders and anyone looking to learn algorithmic trading.

I will show you precisely what to do to solve these situations with simple and easy techniques that anyone can apply.

Why To Have Strong Algorithmic Trading Skills?

Let Me Show You Why To Have Strong Algorithmic Trading Skills:

1. You will succeed in the financial markets.

2. You will master trading.

3. You will build a forex robot.

4. You will learn machine learning.

Requirements:
  • No Prior Knowledge Or Work Is Necessary To Take This Course.
  • Pen And Paper For Precious Notes
Who this course is for:
  • All Forex Trader, Stockbroker, Entrepreneur, Systematic Traders, Short Term Traders
  • Anyone Looking To Learn Algorithmic Trading.
  • This Is Not For People Looking For A Quick Or Lazy Way Of Trading

What you'll learn:

  • Learn Algorithmic Thinking
  • Computational Problem Solving Using Algorithms
  • Algorithmic Design Process
  • Importance of Sorting
  • Array Rotation
  • Insertion Sort
  • Merge & Heap Sort
  • Greedy Algorithms
  • Topological Sorting
  • Breadth & Depth First Traversal
  • Hashing
  • Open Addressing
  • Finding Shortest Path in a graph
  • AVL trees
  • Computational Complexity and Machine Learning

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# Title Duration
1 Introduction to Algorithmic Thinking 05:21
2 Computational Problem Solving Using Algorithms 04:53
3 Algorithmic Design Process 14:10
4 Importance of Sorting 06:53
5 Array Rotation 04:03
6 Insertion Sort 13:26
7 Merge Sort 16:57
8 Sorting Types: Heaps 05:57
9 Heap Sort 12:46
10 Greedy Algorithms 04:42
11 Topological Sorting 04:28
12 Breadth First Traversal 05:31
13 Depth First Traversal 04:53
14 Introduction to Hashing 05:23
15 DIJKSTRA Algorithm with example 05:37
16 Open Addressing 04:29
17 Open Addressing explained with example 03:30
18 Finding Shortest Path In A Graph 02:43
19 AVL trees 02:24
20 AVL Trees Part 2 04:20
21 Computational Complexity and Machine Learning 02:55
22 Machine Learning 05:11

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