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Updated in [July 25th, 2023]
This online course provides an introduction to Forecasting Models and Time Series Analysis in R. It is designed to help students understand the intuition behind time series models and how to apply them in the business world. The course covers the most impactful forecasting model techniques, including Holt-Winters, Sarimax, Facebook Prophet, Neural Networks AutoRegression, and an Ensemble approach. Each technique is explained using words, graphs, and metaphors, with minimal math and Greek alphabet.
The course also provides exercises to apply what is learned immediately. Solutions are coded together line by line, with challenges ranging from predicting the interest in Churrasco (Brazilian BBQ) to the Wikipedia visitors of Udemy. By the end of the course, students will have the knowledge and skills to predict the future.
Course Syllabus
Introduction
Introduction to Forecasting
Seasonal Decomposition
Exponential Smoothing and Holt-Winters
Forecasting Product
ARIMA, SARIMA, and SARIMAX
Facebook Prophet
Facebook Prophet - Parameter Tuning
Neural Networks AutoRegression - Deep Learning
Neural Networks AutoRegression and Deep Learning - Parameter Tuning
Ensemble
EXTRA CONTENT: Time Series Visualization
Bonus Section
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