Time Series Forecasting with Facebook Prophet in Python
About this course
Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. 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.
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What you'll learn
- master time series forecasting using Facebook Prophet
- prepare data for forecasting using Prophet
- fit forecasting models and analyze results
- detect changepoints and manage seasonality
- handle outliers and non-daily data
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