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 IDBAcademy
68,686 already enrolled
898 reviews
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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
- Machine Learning
- Machine Learning Methods
- Model Training
- Statistical Machine Learning
- Deep Learning
- Model Optimization
- Artificial Intelligence and Machine Learning (AI/ML)
- Applied Machine Learning
- Google Cloud Platform
- Technical Analysis
- Finance
- Model Evaluation
- Cloud Platforms
- Supervised Learning
- Financial Trading
- Machine Learning Software
- Time Series Analysis and Forecasting
- Artificial Neural Networks
- Machine Learning Algorithms
- Securities Trading
Details to know

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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.
Reviewed on Jul 10, 2024
Not as prominent or important as the Finance specialization but important factor more so in the lifestyle factor of classification and could be useful to other fortune 500 companies.
Reviewed on Oct 18, 2020
1. Excellent experience in AI lab; 2. Straightforward introduction of the Models; 3. Exercise also has inspiration
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