Overview
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.
Syllabus
Course 1: Introduction to Trading, Machine Learning & GCP
- Offered by Google Cloud and New York Institute of Finance. In this course, you’ll learn about the fundamentals of trading, including the ... Enroll for free.
Course 2: Using Machine Learning in Trading and Finance
- Offered by Google Cloud and New York Institute of Finance. This course provides the foundation for developing advanced trading strategies ... Enroll for free.
Course 3: Reinforcement Learning for Trading Strategies
- Offered by Google Cloud and New York Institute of Finance. In the final course from the Machine Learning for Trading specialization, you ... Enroll for free.
- Offered by Google Cloud and New York Institute of Finance. In this course, you’ll learn about the fundamentals of trading, including the ... Enroll for free.
Course 2: Using Machine Learning in Trading and Finance
- Offered by Google Cloud and New York Institute of Finance. This course provides the foundation for developing advanced trading strategies ... Enroll for free.
Course 3: Reinforcement Learning for Trading Strategies
- Offered by Google Cloud and New York Institute of Finance. In the final course from the Machine Learning for Trading specialization, you ... Enroll for free.
Courses
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In this course, you’ll learn about the fundamentals of trading, including the concept of trend, returns, stop-loss, and volatility. You will learn how to identify the profit source and structure of basic quantitative trading strategies. This course will help you gauge how well the model generalizes its learning, explain the differences between regression and forecasting, and identify the steps needed to create development and implementation backtesters. By the end of the course, you will be able to use Google Cloud Platform to build basic machine learning models in Jupyter Notebooks. 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).
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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).
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In the final course from the Machine Learning for Trading specialization, you will be introduced to reinforcement learning (RL) and the benefits of using reinforcement learning in trading strategies. You will learn how RL has been integrated with neural networks and review LSTMs and how they can be applied to time series data. By the end of the course, you will be able to build trading strategies using reinforcement learning, differentiate between actor-based policies and value-based policies, and incorporate RL into a momentum trading strategy. 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).
Taught by
Jack Farmer and Ram Seshadri
Reviews
3.0 rating, based on 2 Class Central reviews
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The course is just a sales pitch for google cloud platform and its ecosystem. The main intention of this course is just to promote GCP and not really teach you anything. Avoid wasting your time on this.
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Great course with comprehensive review of ML and trading topics. It also includes advanced material such as reinforcement learning for finance. Highly recommended!