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 Syrian Youth Assembly
68,834 already enrolled
Gain insight into a topic and learn the fundamentals.
898 reviews
Intermediate level
Recommended experience
Flexible schedule
5 hours to complete
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
- Artificial Neural Networks
- Applied Machine Learning
- Technical Analysis
- Model Optimization
- Time Series Analysis and Forecasting
- Artificial Intelligence and Machine Learning (AI/ML)
- Model Training
- Machine Learning Software
- Statistical Machine Learning
- Machine Learning Methods
- Deep Learning
- Financial Trading
- Securities Trading
- Finance
- Model Evaluation
- Supervised Learning
- Machine Learning
- Cloud Platforms
- Machine Learning Algorithms
- Google Cloud Platform
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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Showing 3 of 898
LA
Reviewed on Jun 2, 2020
Good introduction to quant theory and ML, labs could be a lot better though, they lack proper explanations and don't cover some of the basics necessary to complete them.
DG
Reviewed on May 4, 2020
The lectures appear to jump around a bit. Looks like it was stitched together from different places. So the course lacks a continuity I have seen in other courses.
AJ
Reviewed on May 1, 2020
This is a very good course because it tuned my already forecasting knowledge to look more into machine learning
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