This course provides the foundation for developing advanced trading strategies using machine learning techniques. In this course, you’ll review the key components that are common to every trading strategy, no matter how complex. You’ll be introduced to multiple trading strategies including quantitative trading, pairs trading, and momentum trading. By the end of the course, you will be able to design basic quantitative trading strategies, build machine learning models using Keras and TensorFlow, build a pair trading strategy prediction model and back test it, and build a momentum-based trading model and back test it.
Using Machine Learning in Trading and Finance
Using Machine Learning in Trading and Finance
This course is part of Machine Learning for Trading Specialization
Instructor: Jack Farmer
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Gain insight into a topic and learn the fundamentals.
376 reviews
Intermediate level
Recommended experience
8 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Design basic quantitative trading strategies
Use Keras and Tensorflow to build machine learning models
Build a pair trading strategy prediction model and back test it.
Build a momentum-based trading model and back test it.
Skills you'll gain
Tools you'll learn
Details to know
Shareable certificate
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Assessments
2 assignments
Taught in English
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This course is part of the Machine Learning for Trading Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 5 modules in this course
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Showing 3 of 376
NS
Reviewed on Jan 26, 2020
I enjoyed the course. Well organized, Good topics.I miss more projects, higher challenge in the projects. (more TODO)There was no practice of Kalman filters.links on the slides are not accessible :-(
CE
Reviewed on Feb 10, 2020
The material is immediately useful and highly practical for people already in financial services.
GY
Reviewed on Jun 27, 2022
Although the often glitches in the Google Cloud platform prevented me to complete the exercises, the course material is very useful.
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