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.
Introduction to Trading, Machine Learning & GCP
Introduction to Trading, Machine Learning & GCP
This course is part of Machine Learning for Trading Specialization
Instructor: Jack Farmer
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Gain insight into a topic and learn the fundamentals.
4.0
(852 reviews)
Intermediate level
Recommended experience
Flexible schedule
Approx. 9 hours
Learn at your own pace
86%
Most learners liked this course
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
Details to know
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Assessments
8 assignments
Taught in English
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This course is part of the Machine Learning for Trading Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
In this module you will be introduced to the fundamentals of trading. You will also be introduced to machine learning. Machine Learning is both an art that involves knowledge of the right mix of parameters that yields accurate, generalized models and a science that involves knowledge of the theory to solve specific types of problems.
What's included
26 videos3 readings4 assignments1 app item
In this module you will be introduced to supervised machine learning and some relevant algorithms commonly applied to trading problems. You will get some hands-on experience building a regression model using BigQuery Machine Learning
What's included
6 videos1 reading1 assignment2 app items
In this module you will learn about ARIMA modeling and how it is applied to time series data. You will get hands-on experience building an ARIMA model for a financial dataset.
What's included
11 videos1 assignment1 app item
In this module you'll learn about neural networks and how they relate to deep learning. You'll also learn how to gauge model generalization using regularization, and cross-validation. Also, you'll be introduced to Google Cloud Platform (GCP). Specifically, you'll be shown how to leverage GCP for implementing trading techniques.
What's included
5 videos1 reading2 assignments1 discussion prompt
Instructor
Instructor ratings
4.4 (185 ratings)
Recommended if you're interested in Machine Learning
New York Institute of Finance
Google Cloud
New York Institute of Finance
New York University
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4.0
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Showing 3 of 852
MF
4
Reviewed on Jan 20, 2020
A good intro to machine learning in finance. I does not goes very deep, but hat some useful exercises and practice with google cloud.
AJ
5
Reviewed on Nov 20, 2020
I thought this was excellent. Some familiarity with standard SQL is needed to get the most benefit from the materials, and the course is clearly aimed at GCP users.
MA
4
Reviewed on Dec 25, 2019
Would be nice to have some extra step at the end of the lad to actually build a trading strategy instead of stopping at the fitting of the model
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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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