2021: Algorithmic Trading with Machine Learning in Python
What you'll learn
- Algorithmic trading
- Machine learning
- Natural Language Processing
- Machine Learning
- Twitter API
- Sentiment Analysis
- Quantitative Background is a plus.
- Experience with Python is a plus.
Hi there, we are James and Sajid. Both of us are working as data scientists for various banks here in London, and we have both gone a long way before arriving at our current position in the market.
Do you wish to become a data scientist and build yourself a strong portfolio? This course will allow you to develop your Python skills tutored by professionals. You will be able to add Natural Language Processing and Deep Learning to your CV and start getting paid for your skills.
In this course, you will learn how to apply the newest methods in machine learning and natural language processing to predictive analysis of the stock market and cryptocurrency.
Use the latest technologies available such as TensorFlow, PlotLy, HuggingFace's Transformers, Flair, spaCy, and many of the essential classics like Pandas, RegEx, Numpy, and more!
We will cover:
- Sentiment Analysis
- Transformers (including Google AI's BERT)
- APIs (including Twitter and Reddit)
- Trading for cryptocurrencies
- Named Entity Recognition (NER)
Take this course if you are learning Python and/or Machine Learning and looking to apply these skills to the stock market. We can't promise to 'fix' on the stock market, but we can promise that you will learn many priceless skills that when applied correctly, can translate to a real benefit both in the job market, and the stock market.
The course is taught by two data scientists from the finance sector. Sajid of Trading 707, who works in Banking and Capital Markets. And James of Aurelio, who specializes in Natural Language Processing (NLP).
Who this course is for:
- Beginner Python developer
- Data scientist
- Finance and Computer Science student
An ML engineer with experience working with Silicon Valley startups, the big four accountancy firms, and other leading financial institutions.
Since entering the world of data science and machine learning, James has specialized in natural language, working on many successful, production-level NLP projects with industry-standard technologies.
Aside from his wide-ranging industry experience, James is a prolific writer and content creator - with the goal of sharing the fascinating world of machine learning (and in particular NLP) with all those that listen. James' articles alone have gathered more than two million viewers.
Coming from a self-taught background, James understands the difficult and winding path towards becoming a data scientist or machine learning engineer. His goal is to deliver content that illuminates that path for others and helps them on their own journey.
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).