This course will help you master time series forecasting using Facebook Prophet in Python. You'll learn how to leverage this powerful tool for accurate predictions and data analysis. By the end of this course, you will be proficient in working with time series data, performing forecasting, and analyzing results to make informed decisions.
The course starts by introducing you to the basics of time series and the importance of forecasting metrics. You’ll get familiar with key concepts like naive forecasting, baselines, and walk-forward validation, which are critical for building robust forecasting models. Understanding these fundamentals will set the stage for the more advanced techniques you’ll explore later in the course.
As you move forward, you’ll dive into Facebook Prophet, learning its key functionalities. You'll explore how to prepare data for Prophet, fit models, and create forecasts. The course covers essential concepts like adding holidays, using exogenous regressors, and performing cross-validation. You’ll also learn how to detect changepoints and handle specific challenges like multiplicative seasonality, outliers, and non-daily data.
This course is perfect for data analysts, scientists, and anyone looking to enhance their forecasting skills using Python. It’s ideal for those with some background in Python and statistics, and is suited for both beginners and intermediate learners interested in time series forecasting.
Overview
Syllabus
- Welcome
- In this module, we will introduce Facebook Prophet and outline the learning objectives of the course. You will also gain an understanding of the course approach and the key components that will be covered throughout.
- Time Series Basics
- In this module, we will introduce the fundamentals of time series and explore key concepts like forecasting metrics, baselines, and walk-forward validation. This section will help build the foundation for understanding how time series forecasting works.
- Facebook Prophet
- In this module, we will dive into Facebook Prophet, exploring its functionality through practical coding sessions. You will learn how to prepare data, fit models, handle holidays and regressors, and perform advanced tasks like changepoint detection and seasonality adjustments.
Taught by
Packt - Course Instructors