Learn the fundamentals of trading, quantitative trading strategies, and the application of machine learning in financial use cases with this comprehensive course. Covering topics such as trend, returns, stop-loss, and volatility, you'll also delve into regression, forecasting, and backtesting. Through the modules, you'll understand the basics of machine learning on Google Cloud Platform, including supervised learning with BigQuery ML, time series and ARIMA modeling, and introduction to neural networks and deep learning.
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This course comprises modules covering the basics of trading, machine learning on Google Cloud Platform, supervised learning with BigQuery ML, time series and ARIMA modeling, and introduction to neural networks and deep learning.
This module provides an introduction to trading with machine learning on Google Cloud Platform. You'll learn about the importance of good data, brief history of ML in quantitative finance, benefits of AI Platform Notebooks, and various quantitative trading strategies.
In this module, you'll delve into supervised learning with BigQuery ML, including forecasting stock prices, choosing the right model, and staying current with BigQuery ML model types. Hands-on labs are included for practical application.
Time Series and ARIMA Modeling module covers the fundamentals of time series, ARIMA modeling, sensitivity of trading strategy, and building an ARIMA model for a financial dataset using practical lab exercises.
This module introduces neural networks and deep learning, covering the history of ML, overfitting, validation, and training data splits. It also includes a course recap and a preview of the next course, along with practical examples and a recap quiz.
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