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
Access provided by New York State Department of Labor
60,632 already enrolled
Gain insight into a topic and learn the fundamentals.
4.0
(872 reviews)
Intermediate level
Recommended experience
Flexible schedule
Approx. 9 hours
Learn at your own pace
85%
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
- Google Cloud Platform
- Forecasting
- Machine Learning
- Financial Trading
- Quantitative Research
- Artificial Neural Networks
- Time Series Analysis and Forecasting
- Predictive Modeling
- Regression Analysis
- Artificial Intelligence and Machine Learning (AI/ML)
- Applied Machine Learning
- Machine Learning Algorithms
- Financial Forecasting
- Technical Analysis
- Supervised Learning
- Securities Trading
- Deep Learning
- Financial Modeling
- Statistical Machine Learning
Details to know
Shareable certificate
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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 (189 ratings)
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4.0
872 reviews
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Showing 3 of 872
AJ
5
Reviewed on May 2, 2020
This is a very good course because it tuned my already forecasting knowledge to look more into machine learning
MS
5
Reviewed on Jan 30, 2020
Excellent! But, I am missing some of the prerequisites since I just wanted to take a chance and try things out, but feel like proceeding further might lead to some stumbling blocks.
BY
5
Reviewed on Oct 19, 2020
1. Excellent experience in AI lab; 2. Straightforward introduction of the Models; 3. Exercise also has inspiration
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