About this Course

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Flexible deadlines
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Intermediate Level
Approx. 7 hours to complete
Subtitles: English

Skills you will gain

Algorithmic TradingPython ProgrammingMachine Learning
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 7 hours to complete
Subtitles: English

Offered by

New York Institute of Finance logo

New York Institute of Finance

Google Cloud logo

Google Cloud

Syllabus - What you will learn from this course


Week 1

3 hours to complete

Introduction to Quantitative Trading and TensorFlow

3 hours to complete
10 videos (Total 46 min), 1 reading, 2 quizzes
10 videos
Basic Trading Strategy Entries and Exits Endogenous Exogenous7m
Basic Trading Strategy Building a Trading Model2m
Advanced Concepts in Trading Strategies6m
Introduction to TensorFlow1m
Estimator API3m
Predicting real estate house values using simple data set5m
Estimator API Lab Introduction39s
Getting Started with Google Cloud Platform and Qwiklabs3m
Estimator API Lab Solution10m
1 reading
Welcome to Using Machine Learning in Trading and Finance10m
1 practice exercise
Understand Quantitative Strategies

Week 2

2 hours to complete

Build a Pair Trading Strategy Prediction Model

2 hours to complete
9 videos (Total 56 min)
9 videos
Picking Pairs4m
Picking Pairs with Clustering8m
How to Implement a Pair Strategy9m
Evaluate Results of a Pair Trade6m
Backtesting and Avoiding Overfitting6m
Next Steps: Improvements to Your Pairs Strategy5m
Pairs Trading Lab Introduction30s
Pairs Trading Lab Solution7m
1 practice exercise
Pairs Trading Strategy and Backtesting

Week 3

2 hours to complete

Build a Momentum-based Trading System

2 hours to complete
13 videos (Total 77 min)
13 videos
Building a Momentum Trading Model7m
Define the Problem9m
Collect the Data2m
Creating Features3m
Split the Data3m
Selecting a Machine Learning Algorithm3m
Backtest on Unseen Data1m
Understanding the Code: Simple ML Strategies to Generate Trading Signal9m
Kalman Filter Introduction11m
Kalman Filter Trading Applications6m
Momentum Trading Lab Introduction43s
Momentum Trading Lab Solution7m



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About the Machine Learning for Trading Specialization

This Specialization is for finance professionals, including but not limited to hedge fund traders, analysts, day traders, those involved in investment management or portfolio management, and anyone interested in gaining greater knowledge of how to construct effective trading strategies using Machine Learning. Alternatively, this specialization can be for machine learning professionals who seek to apply their craft to quantitative trading strategies. The courses will teach you how to create various trading strategies using Python. By the end of the Specialization, you will be able to create quantitative trading strategies that you can train and implement. You will also learn how to use reinforcement learning strategies to create algorithms that can update and train themselves. To be successful in this Specialization, you should have a basic competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL will be helpful. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and basic knowledge of financial markets (equities, bonds, derivatives, market structure, hedging)....
Machine Learning for Trading

Frequently Asked Questions

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

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  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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