Description
Machine Learning for Trading Specialization is a series of training on the principles of machine learning for trading in financial markets published by Coursera. Algorithmic and quantitative trading are two very popular approaches in buying and selling stocks and assets. These two approaches use different techniques in machine learning and statistical science for automated ordering and have gained a lot of fans around the world.
This educational series consists of three completely separate courses and was designed by two Google cloud services organizations (Google Cloud) and the New York Institute of Finance. This training course is for general use and almost all people active in the capital market such as hedge fund traders, analysts, day traders, managers of investment companies, etc. can benefit from it equally.
Various strategies can be designed for trading in the financial markets, but strategy design is only a small and initial part of the story, and to implement it, we must use the Python programming language and the principles and basics of machine learning science. In quantitative trading, we are dealing with a completely intelligent robot that, during its financial day, places a set of orders on the system based on the parameters set, and the overall result is positive.
What you will learn in the Machine Learning for Trading Specialization training series:
- Economics and finance
- Trading and buying and selling assets in different financial markets
- Invest in different financial markets
- Principles and basics of machine learning
- Algorithmic trading and quantitative trading
- Python programming language
- Construction and development of reinforcement learning model
- Optimization of different trading algorithms
- Development and optimization of different trading strategies
- And …
Course details
Publisher: Coursera
Instructor: Jack Farmer
Language: English
Provider institution/university: Google Cloud services and New York Institute of Finance
Education level: Intermediate
Number of courses: 3
Duration of education: with Assuming 4 hours of work per week for about 3 months
Courses available in the Machine Learning for Trading Specialization collection
Course 1
Introduction to Trading, Machine Learning & GCP
Course 2
Using Machine Learning in Trading and Finance
Course 3
Reinforcement Learning for Trading Strategies
Machine Learning for Trading Course prerequisites
What background knowledge is necessary?
To be successful in this course, you should have a basic competency in Python programming and familiarity with the Scikit Learn, Statsmodels and Pandas library. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging).
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Installation guide
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English subtitle
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This educational series consists of 3 separate courses.
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Introduction to Trading, Machine Learning & GCP
Using Machine Learning in Trading and Finance
Reinforcement Learning for Trading Strategies
Download course 1 – 393 MB
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