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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