Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
10 Hour(s) 38 Minute(s)
Language
English
Rating
Course Overview
Learn the cutting-edge in NLP with transformer models and how to apply them to the world of algorithmic trading
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:
- TensorFlow
- 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).
Course Content
- 9 section(s)
- 54 lecture(s)
- Section 1 Introduction
- Section 2 Python 101
- Section 3 Data Visualisation Advanced for Algorithmic Trading
- Section 4 Stay Connected to The Market
- Section 5 Introduction to TensorFlow
- Section 6 Introduction to Sentiment Analysis and Twitter API
- Section 7 Advanced Sentiment Analysis
- Section 8 Identifying Entities with NER
- Section 9 Hot and Trendy Shares Detector Prototype (Bonus)
What You’ll Learn
- Algorithmic trading, Python, Machine learning, Programming, Finance, Trading, Keras, Natural Language Processing, Machine Learning, TensorFlow, Twitter API, Sentiment Analysis
Reviews
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DDavid M Martnick
Some stuff was outdated as to be expected. Some stuff in the NER section needed to be recoded becuase the script did not work and to move on further with the course, it was required to be in a format that matched the instructor. In the Hot and Trendy Prototype, the yahoo finance library was outdated. I also tried figuring out how he got the internet tab with the JSON script with the URL but there was no instruction on how he got to that point. I ended up using scripts from other people to effectively do the same thing the instructor was trying to do.
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GGurbaxeesh Singh Ahuja
Well structured course . Eloquent mentor ...comprehesively covered the subject...
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AAnonymized User
Mr. Lhessani is difficult to follow, because he tends to type on the very bottom of the screen and immediately scroll away. Mr. Briggs is clearer but he often does not explain what he's trying to do and why, so you catch only at the very end what's the code for. The topic is interesting but it was difficult for me to follow this course.
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CChandra S Gorentla
This course is less about algorithmic trading and more about getting data from different resources and doing sentiment analysis on the data. Also I could not find the source code used by instructors but they provide the data they used in their lectures. There are a couple of questions about source code unanswered.
