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Machine Learning – Quant Trading

STUDY365

Certificate , Machine Learning

Course Description

Overview

This ’Quant Trading Using Machine Learning’ online training course takes a completely practical approach to applying Machine Learning techniques to Quant Trading. The focus is on practically applying ML techniques to develop sophisticated Quant Trading models. From setting up your own historical price database in MySQL, to writing hundreds of lines of Python code, the focus is on doing from the get-go. Supplemental Material included!

Learning with Study 365 has many advantages. The course material is delivered straight to you and can be adapted to fit in with your lifestyle. It is created by experts within the industry, meaning you are receiving accurate information, which is up-to-date and easy to understand.

This course is comprised of professional learning materials, all delivered through a system that you will have access to 24 hours a day, 7 days a week for 365 days (12 months).

Overview This ’Quant Trading Using Machine Learning’ online training course takes a completely practical approach to applying Machine Learning techniques to Quant Trading. The focus is on practically applying ML techniques to develop sophisticated Quant Trading models. From setting up your own historical price database in MySQL, to writing hundreds of...

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Course Content

Course Curriculum

Free Introduction1: You, This Course & Us2: Developing Trading Strategies in Excel3: Setting up your Development Environment4: Setting up a Price Database5: Decision Trees, Ensemble Learning & Random Forests6: A Trading Strategy as Machine Learning Classification7: Feature Engineering8: Engineering a Complex Feature – A Categorical Variable with Past Trends9: Building a Machine Learning Classifier in Python10: Nearest Neighbors Classifier11: Gradient Boosted Trees12: Introduction to Quant Trading

Course Reviews

Course Curriculum Free Introduction1: You, This Course & Us2: Developing Trading Strategies in Excel3: Setting up your Development Environment4: Setting up a Price Database5: Decision Trees, Ensemble Learning & Random Forests6: A Trading Strategy as Machine Learning Classification7: Feature Engineering8: Engineering a Complex Feature – A Categorical Variable with Past...

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Entry Requirements

Entry Requirement:

  • Learners must be age 16 or over and should have a basic understanding of the English Language, numeracy, literacy, and ICT.
  • Working knowledge of Python is necessary if you want to run the source code that is provided.
  • Basic knowledge of machine learning, especially Machine Learning classification techniques, would be helpful but it’s not

Entry Requirement: Learners must be age 16 or over and should have a basic understanding of the English Language, numeracy, literacy, and ICT. Working knowledge of Python is necessary if you want to run the source code that is provided. Basic knowledge of machine learning, especially Machine Learning classification techniques, would be...

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Assessment Methods

Method of Assessment:

At the end of each module, you will have one assignment to be submitted (you need a mark of 65% to pass) and you can submit the assignment at any time. You will only need to pay £19 for assessment and certification when you submit the assignment. You will receive the results within 72 hours of submittal, and will be sent a certificate in 7-14 days if you have successfully passed.

Method of Assessment: At the end of each module, you will have one assignment to be submitted (you need a mark of 65% to pass) and you can submit the assignment at any time. You will only need to pay £19 for assessment and certification when you submit the assignment. You will receive the results within 72 hours of submittal, and will be sent a certificate in...

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Additional Information

Certification:

Successful candidates will be awarded a certificate for Machine Learning – Quant Trading.

Certification:

Successful candidates will be awarded a certificate for Machine Learning – Quant Trading.