Introduction to Algorithmic Trading
What you'll learn
- Algorithmic Trading
- Quantitative finance
- Financial Trading
- Volatility analysis
- Quant Trading
- Ichimoku kinko hyo
- Bollinger bands
- A desktop computer (Windows, Mac, or Linux) capable of storing and running Anaconda. The course will walk you through installing the necessary free software.
- Mathematical foundation is a plus but not mandatory
- Basic knowledge about Python is a plus but not mandatory.
- Knowledge about normal/gaussian distribution is a plus but not mandatory
Please refer to the latest version of the course. This version has been updated under the name: "2021:learn algorithmic trading in one day".
The second part of this course can be found within our profile. This version as some packages needed updates will be removed from the marketplace in the next 6 months.
The second version of this course covers the latest machine learning algorithm, plus two extra algorithm implementation.
This course will allow you to develop your Python skills tutored by professionals. You will be able to add Trading Technical Analysis and Algorithmic Trading to your CV and start getting paid for your skills.
What you will learn from this course:
- Develop your first PROFITABLE algorithms to predict the market. (Stock exchange (US, Indian, Dax, CAC40) + Crypto)
- Step up in data visualisation to create a portfolio for a career switch
- Learn how to import market data.
- Getting connected to the US stock exchange live and get market data with less than one-second lag. (The only course of proposing this option).
- Develop your first trading strategies on Python such as Ichimoku Kinko Hyo or Bollinger Bands with Live Trading Examples. (The only course of proposing this option).
Thank you for understanding.
Sajid Lhessani (Algo Trading instructor).
Who this course is for:
- Beginner Python developers curious about algorithmic trading.
- Beginner Python developers curious about data science.
- Finance student
Trading 707 is a combination of a data scientist and a trader.
We are both working and living in London.
We felt tired or enrolling in courses and receiving tips from people without any professional experience. That is why we chose to share with you our own trick, that we are using on a daily basis at work.
If you want to integrate our community, feel free to reach us.
If you want to know more about our in-field experience, you can google us or find us on LinkedIn (Sajid Lhessani, Sami Sebai).