This course is part of the Machine Learning for Trading Specialization

3.9
stars
322 ratings

Jack Farmer

20,331 already enrolled

Offered By

New York Institute of Finance

Google Cloud

Machine Learning for Trading SpecializationNew York Institute of Finance

About this Course

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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.
To be successful in this course, you should have advanced competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL is recommended. 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).

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

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Start instantly and learn at your own schedule.

Course 2 of 3 in the

Machine Learning for Trading Specialization

Intermediate Level

Basic competency in Python, familiarity with the Scikit Learn, Statsmodels and Pandas library.
Familiarity with statistics, financial markets, ML

Approx. 18 hours to complete

English

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What you will 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 will gain

Algorithmic Trading
Python Programming
Machine Learning

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 2 of 3 in the

Machine Learning for Trading Specialization

Intermediate Level

Basic competency in Python, familiarity with the Scikit Learn, Statsmodels and Pandas library.
Familiarity with statistics, financial markets, ML

Approx. 18 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

4.45/5 (49 Ratings)

Jack Farmer

Curriculum Director

New York Institute of Finance

84,040 Learners

13 Courses

Offered by

New York Institute of Finance

The New York Institute of Finance (NYIF), is a global leader in training for financial services and related industries. Started by the New York Stock Exchange in 1922, it now trains 250,000+ professionals in over 120 countries. NYIF courses cover everything from investment banking, asset pricing, insurance and market structure to financial modeling, treasury operations, and accounting. The institute has a faculty of industry leaders and offers a range of program delivery options, including self-study, online courses, and in-person classes. Its US customers include the SEC, the Treasury, Morgan Stanley, Bank of America and most leading worldwide banks.

Google Cloud

We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.

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Syllabus - What you will learn from this course

Content Rating85%(1,424 ratings)

Week1

Week 1

1 hour to complete

Introduction to Quantitative Trading and TensorFlow

1 hour to complete

4 videos (Total 23 min), 1 reading, 1 quiz

4 hours to complete

Introduction to TensorFlow

4 hours to complete

11 videos (Total 50 min)

11 videos

Overview1mIntroduction to TensorFlow6mTensorFlow API Hierarchy4mComponents of tensorflow Tensors and Variables8mGetting Started with Google Cloud Platform and Qwiklabs3mLab Intro Writing low-level TensorFlow programs43sWorking in-memory and with files3mTraining on Large Datasets with tf.data API4mGetting the data ready for model training6mEmbeddings8mLab Intro Manipulating data with TensorFlow Dataset API34s

Week2

Week 2

3 hours to complete

Training neural networks with Tensorflow 2 and Keras

3 hours to complete

12 videos (Total 53 min)

Week3

Week 3

6 hours to complete

Build a Momentum-based Trading System

Momentum trading is a strategy in which traders buy or sell assets according to the strength of recent price trends. Price momentum is similar to momentum in physics, where mass multiplied by velocity determines the persistence with which an object will follow its current path (like a heavy train on a track). In financial markets, however, momentum is determined by other factors like trading volume and rate of price changes. Momentum traders bet that an asset price that is moving strongly in a given direction will continue to move in that direction until the trend loses strength or reverses. This module teaches you all about momentum trading.

6 hours to complete

12 videos (Total 68 min), 1 reading, 2 quizzes

12 videos

Introduction to Momentum Trading9mIntroduction to Hurst8mBuilding a Momentum Trading Model7mDefine the Problem9mCollect the Data2mCreating Features3mSplit the Data3mSelecting a Machine Learning Algorithm3mBacktest on Unseen Data1mUnderstanding the Code: Simple ML Strategies to Generate Trading Signal9mLab Intro: Momentum Trading43sMomentum Trading Lab Solution7m

1 reading

Hurst Exponent and Trading Signals Derived from Market Time Series10m

Week4

Week 4

5 hours to complete

Build a Pair Trading Strategy Prediction Model

5 hours to complete

11 videos (Total 74 min)

11 videos

Introduction to Pair Trading7mPicking Pairs4mPicking Pairs with Clustering8mHow to implement a Pair Trading Strategy9mEvaluate Results of a Pair Trade6mBacktesting and Avoiding Overfitting6mNext Steps: Improvements to your Pairs Strategy5mLab Intro: Pairs Trading30sLab Solution: Pairs Trading7mKalman Filter Introduction11mKalman Filter Trading Applications6m

1 practice exercise

Pairs Trading Strategy concepts

Reviews

3.9

88 reviews

5 stars
44.58%
4 stars
26.93%
3 stars
14.24%
2 stars
7.43%
1 star
6.81%

TOP REVIEWS FROM USING MACHINE LEARNING IN TRADING AND FINANCE

by APJul 6, 2021

It's not deep enough to understand how to implement ML in algorithmic trading, but the course explains some helpful concepts like pairs trading and Kalmar filter.

by SGMay 23, 2020

I wish better examples to cover everything was said during the lectures

by OKNov 14, 2021

If that unrelated Google Cloud part were thrown away, it would be a decent course.

by MFJan 19, 2020

Very informative. I does not go too much in details but you get a lot of insight about trading and using ML in trading strategies

View all reviews

About the Machine Learning for Trading Specialization

This 3-course Specialization from Google Cloud and New York Institute of Finance (NYIF) 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 (ML) and Python. Alternatively, this program can be for Machine Learning professionals who seek to apply their craft to quantitative trading strategies. By the end of the Specialization, you'll understand how to use the capabilities of Google Cloud to develop and deploy serverless, scalable, deep learning, and reinforcement learning models to create trading strategies that can update and train themselves. As a challenge, you're invited to apply the concepts of Reinforcement Learning to use cases in Trading. This program is intended for those who have an understanding of the foundations of Machine Learning at an intermediate level. To successfully complete the exercises within the program, you should have advanced competency in Python programming and familiarity with pertinent libraries for Machine Learning, such as Scikit-Learn, StatsModels, and Pandas; a solid background in ML and statistics (including regression, classification, and basic statistical concepts) and basic knowledge of financial markets (equities, bonds, derivatives, market structure, and hedging). Experience with SQL is recommended.

Frequently Asked Questions

When will I have access to the lectures and assignments?
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:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
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.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

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