Google Cloud
New York Institute of Finance
Machine Learning for Trading Specialization
Google Cloud
New York Institute of Finance

Machine Learning for Trading Specialization

Start Your Career in Machine Learning for Trading. Learn the machine learning techniques used in quantitative trading.

Jack Farmer

Instructor: Jack Farmer

Included with Coursera Plus

Get in-depth knowledge of a subject

(1,111 reviews)

Intermediate level

Recommended experience

1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject

(1,111 reviews)

Intermediate level

Recommended experience

1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers

What you'll learn

  • Understand the structure and techniques used in machine learning, deep learning, and reinforcement learning (RL) strategies.

  • Describe the steps required to develop and test an ML-driven trading strategy.

  • Describe the methods used to optimize an ML-driven trading strategy.

  • Use Keras and Tensorflow to build machine learning models.

Overview

What’s included

Shareable certificate

Add to your LinkedIn profile

Taught in English
10 practice exercises

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Google Cloud

Specialization - 3 course series

What you'll learn

  • Understand the fundamentals of trading, including the concepts of trend, returns, stop-loss, and volatility.

  • Define quantitative trading and the main types of quantitative trading strategies.

  • Understand the basic steps in exchange arbitrage, statistical arbitrage, and index arbitrage.

  • Understand the application of machine learning to financial use cases.

Skills you'll gain

Artificial Neural Networks, Deep Learning, Google Cloud Platform, Machine Learning, Financial Trading, Quantitative Research, Machine Learning Algorithms, Statistical Machine Learning, Forecasting, Time Series Analysis and Forecasting, Securities Trading, Artificial Intelligence and Machine Learning (AI/ML), Financial Forecasting, Financial Modeling, Supervised Learning, Applied Machine Learning, Technical Analysis, Finance, and Regression Analysis

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

Financial Trading, Technical Analysis, Applied Machine Learning, Python Programming, Machine Learning, Deep Learning, Predictive Modeling, Keras (Neural Network Library), Data Pipelines, Tensorflow, Financial Market, Securities Trading, Market Trend, and Performance Metric

What you'll learn

  • Understand the structure and techniques used in reinforcement learning (RL) strategies.

  • Understand the benefits of using RL vs. other learning methods.

  • Describe the steps required to develop and test an RL trading strategy.

  • Describe the methods used to optimize an RL trading strategy.

Skills you'll gain

Reinforcement Learning, Deep Learning, Applied Machine Learning, Financial Trading, Time Series Analysis and Forecasting, Markov Model, Financial Market, Artificial Intelligence and Machine Learning (AI/ML), Portfolio Management, Machine Learning, and Artificial Neural Networks

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Jack Farmer
New York Institute of Finance
13 Courses165,182 learners

Offered by

Google Cloud

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