Time Series Forecasting with Facebook Prophet Practice Exam

Time Series Forecasting with Facebook Prophet Practice Exam

About the Time Series Forecasting with Facebook Prophet Exam

Time Series Forecasting with Facebook Prophet is a powerful technique for predicting future trends based on historical data. Prophet, an open-source library developed by Meta, is designed for handling time series data with trends, seasonality, and holidays. It offers an intuitive interface, automatic handling of missing values, and robust performance for business and financial forecasting. Ideal for analysts and data scientists, Prophet simplifies forecasting tasks, making it easier to generate accurate predictions with minimal parameter tuning.

Skills Required

• Basic Python Knowledge – Understanding of variables, functions, and data structures.
• Fundamentals of Statistics – Knowledge of mean, variance, and time series concepts.
• Understanding of Pandas and NumPy – Familiarity with handling and manipulating time series data.
• Basic Data Visualization Skills – Experience with Matplotlib or Seaborn for plotting time series trends.
• Familiarity with Machine Learning Concepts – Helpful for understanding forecasting models and evaluation metrics.
• Installation of Facebook Prophet – Ability to set up Prophet and its dependencies in a Python environment.

Knowledge Gained 

• Understanding the fundamentals of time series forecasting and its real-world applications.
• Proficiency in using Facebook Prophet for trend, seasonality, and holiday-based forecasting.
• Skills to preprocess and clean time series data for accurate predictions.
• Ability to visualize and interpret forecast results using Python libraries like Matplotlib and Seaborn.
• Knowledge of hyperparameter tuning to optimize Prophet models for better accuracy.
• Experience in handling missing values and outliers in time series data.
• Understanding of evaluation metrics like MAE, RMSE, and MAPE to assess model performance.
• Practical application of Prophet for business, finance, and demand forecasting scenarios.

Who should take the Exam?

• Data scientists and analysts interested in time series forecasting and predictive modeling.
• Business analysts who want to apply forecasting techniques to improve decision-making.
• Machine learning practitioners looking to expand their knowledge in time series analysis.
• Financial analysts and economists working with financial data and trends.
• Software developers and engineers who want to integrate time series forecasting into applications.
• Students and job seekers aiming to enhance their skills in data science and predictive analytics.
• Anyone interested in learning and applying advanced forecasting techniques using Facebook Prophet.

Course Outline

Welcome

• Introduction
• Outline

Time Series Basics

• Time Series Basics Section Introduction
• Forecasting Metrics
• The Naive Forecast and the Importance of Baselines
• Walk-Forward Validation
• Suggestion Box

Facebook Prophet

• How Does Prophet Work?
• Prophet: Code Preparation
• Prophet in Code: Data Preparation
• Prophet in Code: Fit, Forecast, Plot
• Prophet in Code: Holidays and Exogenous Regressors
• Prophet in Code: Cross-Validation
• Prophet in Code: Changepoint Detection
• Prophet: Multiplicative Seasonality, Outliers, Non-Daily Data
• (The Dangers of) Prophet for Stock Price Prediction
• Prophet Section Summary