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Algorithmic Trading A-Z with Python, Machine Learning & AWS

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  • 47,514 Students
  • Updated 12/2025
4.5
(4,237 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Language
English
Taught by
Alexander Hagmann
Rating
4.5
(4,237 Ratings)

Course Overview

Algorithmic Trading A-Z with Python, Machine Learning & AWS

Build your own truly Data-driven Day Trading Bot | Learn how to create, test, implement & automate unique Strategies.

Welcome to the most comprehensive Algorithmic Trading Course. It´s the first 100% Data-driven Trading Course!

Did you know that 75% of retail Traders lose money with Day Trading? (some sources say >95%)

For me as a Data Scientist and experienced Finance Professional this is not a surprise. Day Traders typically do not know/follow the five fundamental rules of (Day) Trading. This Course covers them all in detail!


1. Know and understand the Day Trading Business

Don´t start Trading if you are not familiar with terms like Bid-Ask Spread, Pips, Leverage, Margin Requirement, Half-Spread Costs, etc.

Part 1 of this course is all about Day Trading A-Z with the Brokers Oanda, Interactive Brokers, and FXCM. It deeply explains the mechanics, terms, and rules of Day Trading (covering Forex, Stocks, Indices, Commodities, Baskets, and more).


2. Use powerful and unique Trading Strategies

You need to have a Trading Strategy. Intuition or gut feeling is not a successful strategy in the long run (at least in 99.9% of all cases). Relying on simple Technical Rules doesn´t work either because everyone uses them.

You will learn how to develop more complex and unique Trading Strategies with Python. We will combine simple and also more complex Technical Indicators and we will also create Machine Learning- and Deep Learning- powered Strategies. The course covers all required coding skills (Python, Numpy, Pandas, Matplotlib, scikit-learn, Keras, Tensorflow) from scratch in a very practical manner.

3. Test your Strategies before you invest real money (Backtesting / Forward Testing)

Is your Trading Strategy profitable? You should rigorously test your strategy before 'going live'.

This course is the most comprehensive and rigorous Backtesting / Forward Testing course that you can find.

You will learn how to apply Vectorized Backtesting techniques, Iterative Backtesting techniques (event-driven), live Testing with play money, and more. And I will explain the difference between Backtesting and Forward Testing and show you what to use when. The backtesting techniques and frameworks covered in the course can be applied to long-term investment strategies as well!


4. Take into account Trading Costs - it´s all about Trading Costs!

"Trading with zero commissions? Great!" ... Well, there is still the Bid-Ask-Spread and even if 2 Pips seem to be very low, it isn´t!

The course demonstrates that finding profitable Trading Strategies before Trading Costs is simple. It´s way more challenging to find profitable Strategies after Trading Costs! Learn how to include Trading Costs into your Strategy and into Strategy Backtesting / Forward Testing. And most important: Learn how you can control and reduce Trading Costs.

5. Automate your Trades

Manual Trading is error-prone, time-consuming, and leaves room for emotional decision-making.

This course teaches how to implement and automate your Trading Strategies with Python, powerful Broker APIs, and Amazon Web Services (AWS). Create your own Trading Bot and fully automate/schedule your trading sessions in the AWS Cloud!


Finally... this is more than just a course on automated Day Trading:

  • the techniques and frameworks covered can be applied to long-term investing as well.

  • it´s an in-depth Python Course that goes beyond what you can typically see in other courses. Create Software with Python and run it in real-time on a virtual Server (AWS)!

  • we will feed Machine Learning & Deep Learning Algorithms with real-time data and take ML/DL-based actions in real-time!

What are you waiting for? Join now. As always, there is no risk for you as I provide a 30-Days-Money-Back Guarantee!

Thanks and looking forward to seeing you in the Course!

Course Content

  • 37 section(s)
  • 526 lecture(s)
  • Section 1 Getting Started
  • Section 2 +++ PART 1: Day Trading, Online Brokers and APIs +++
  • Section 3 Day Trading with OANDA A-Z: a Deep Dive
  • Section 4 Stocks and FOREX Trading with Interactive Brokers (IBKR)
  • Section 5 FOREX Day Trading with FXCM
  • Section 6 Installing Python and Jupyter Notebooks
  • Section 7 Excursus: How to avoid and debug Coding Errors (don´t skip!)
  • Section 8 API Trading with Python and Online Brokers- an Introduction
  • Section 9 Conclusion and Outlook
  • Section 10 +++ PART 2: Pandas for Financial Data Analysis and Introduction to OOP +++
  • Section 11 Introduction to Time Series Data in Pandas
  • Section 12 Financial Data Analysis with Python and Pandas - a (deep) Introduction
  • Section 13 Advanced Topics
  • Section 14 Object Oriented Programming (OOP): Creating a Financial Analysis Class
  • Section 15 +++ PART 3: Defining and Testing Trading Strategies +++
  • Section 16 Defining and Backtesting SMA Strategies
  • Section 17 Defining and Backtesting simple Momentum/Contrarian Strategies
  • Section 18 Defining and Backtesting Mean-Reversion Strategies (Bollinger)
  • Section 19 Trading Strategies powered by Machine Learning - Regression
  • Section 20 Trading Strategies powered by Machine Learning - Classification
  • Section 21 Advanced Backtesting Techniques
  • Section 22 +++ PART 4: Real-time Implementation and Automation of Strategies +++
  • Section 23 Implementation and Automation with OANDA (UPDATED!)
  • Section 24 Implementation and Automation with IBKR
  • Section 25 Implementation and Automation with FXCM
  • Section 26 Cloud Deployment (AWS) | Scheduling Trading Sessions | Full Automation
  • Section 27 +++ PART 5: Expert Tips & Tricks, Case Studies and more +++
  • Section 28 Trading Hours, Spreads and Granularity - control and limit Trading Costs!
  • Section 29 Working with two or many Strategies (Combination)
  • Section 30 A Machine Learning-powered Strategy A-Z (DNN)
  • Section 31 Error Handling: How to make your Trading Bot more stable and reliable
  • Section 32 Adding Stop Loss and Take Profit to the Trading Bot
  • Section 33 +++ APPENDIX: Python Crash Course +++
  • Section 34 Appendix 1: Python (& Finance) Basics
  • Section 35 Appendix 2: User-defined Functions (required for OOP)
  • Section 36 Appendix 3: Numpy, Pandas, Matplotlib and Seaborn Crash Course
  • Section 37 What´s next? (outlook and additional resources)

What You’ll Learn

  • Build automated Trading Bots with Python and Amazon Web Services (AWS), Create powerful and unique Trading Strategies based on Technical Indicators and Machine Learning / Deep Learning., Rigorous Testing of Strategies: Backtesting, Forward Testing and live Testing with paper money., Fully automate and schedule your Trades on a virtual Server in the AWS Cloud., Truly Data-driven Trading and Investing., Python Coding and Object Oriented Programming (OOP) in a way that everybody understands it., Coding with Numpy, Pandas, Matplotlib, scikit-learn, Keras and Tensorflow., Understand Day Trading A-Z: Spread, Pips, Margin, Leverage, Bid and Ask Price, Order Types, Charts & more., Day Trading with Brokers OANDA, Interactive Brokers (IBKR) and FXCM., Stream high-frequency real-time Data., Understand, analyze, control and limit Trading Costs., Use powerful Broker APIs and connect with Python.


Reviews

  • T
    Tomoko Nakasuji
    4.0

    I truly appreciate this course that cultivated the depth of my understanding of utilizing the 3rd-party trader platforms with python. OANDA, IKBR, and FXCM are all major individual-to-institution platforms along with other AWS Console, etc. Overall, each platform requires different techniques to use appropriately, but this course clearly articulated them.

  • S
    Shobha Shivaprasad
    5.0

    teaching method and explanation is very clear

  • J
    John L
    5.0

    Good content. I learn this course because it teach IB async coding. Appreciate the code and course are up-to-date.

  • C
    Cesar Arturo Anton De La Cruz
    5.0

    buen análisis del paso a paso. útil para ampliar los conocimientos.

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