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Data & Feature Engineering for Trading

1660 Learners
11 hours
How many times have you created a strategy that performed well during backtesting, however failed to make money in the real markets? An essential course to create robust machine learning strategies which can be executed on trading platforms. This course teaches the data cleaning aspects on financial datasets and with real-world examples.
Level
Intermediate
Authors
Dr. Ernest P. Chan
Dr. Roger Hunter
Price Lifetime Access Limited Time Offer

₹10150/-₹40599/-

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  • Skills Covered
  • Learning Track
  • Prerequisites
  • Syllabus
  • About author
  • Testimonials
  • Faqs

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Course Features

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  • Interactive Coding Exercises
    Interactive Coding Exercises

    Interactive Coding Practice

  • Get Certified
    Get Certified

    Get Certified

learning track 4

This course is a part of the Learning Track: Machine Learning & Deep Learning in Trading Beginners

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Prerequisites

You should be familiar with basic machine learning principles such as train and test datasets. There are no prerequisites as such and anyone who is familiar with financial markets data can enroll in the course.

After this course you’ll be able to

  • Preprocess price data to resolve outliers, duplicate values, multiple stock classes, survivorship bias, and look-ahead bias issues.
  • Work with sentiment data to identify structural break and aggregate categorical features.
  • Examine fundamental data and resolve multiple data merging issues.
  • Create features and target variables for machine learning models. 
  • Explain various challenges associated with the financial data

Syllabus

about author

Dr. Ernest P. Chan
Dr. Ernest P. Chan
Dr. Ernest Chan is the Managing Member of QTS Capital Management, LLC., a commodity pool operator and trading advisor. QTS manages a hedge fund as well as individual accounts. He has worked in IBM human language technologies group where he developed natural language processing system which was ranked 7th globally in the defense advanced research project competition. He also worked with Morgan Stanley’s Artificial intelligence and data mining group where he developed trading strategies.
Dr. Roger Hunter
Dr. Roger Hunter
Dr. Roger Hunter is the Chief Technology Officer of QTS. He is responsible for designing high-performance automated execution system that achieved negative slippage. Roger is a serial entrepreneur, having founded profitable hedge funds and software firms. Roger was formerly professor of mathematics at New Mexico State University, and he obtained his Ph.D. in Mathematics from Australian National University.
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