Time Series Forecasting with Facebook Prophet Practice Exam

Time Series Forecasting with Facebook Prophet Practice Exam

Time Series Forecasting with Facebook Prophet is a method used to predict future trends based on past data. A “time series” simply means data collected over time, like daily sales, stock prices, or website traffic. Facebook Prophet is a tool created by Meta (Facebook) that makes forecasting easy, even for people who aren’t experts in statistics. It can identify patterns like seasonality (weekly, monthly, yearly trends), holidays, and other factors that influence data.
In simple words, if you’ve ever tried to guess how many people will visit your shop next week based on how many came last week, that’s forecasting. Facebook Prophet does this at a professional level, using powerful algorithms to provide accurate predictions in a user-friendly way. It helps businesses, researchers, and organizations plan better by knowing what to expect in the future.

Who should take the Exam?

This exam is ideal for:

• Data Analysts
• Business Analysts
• Data Scientists
• Financial Analysts
• Market Researchers
• Operations Managers

Skills Required

• Basic knowledge of Python or R
• Data handling and visualization
• Interest in business analytics or forecasting

Knowledge Gained

• Building forecasting models with Facebook Prophet
• Handling seasonality, holidays, and special events in predictions
• Evaluating model accuracy
• Using forecasts to support decision-making
• Applying forecasting in real-world domains like finance, retail, and marketing

Course Outline

The Time Series Forecasting with Facebook Prophet Exam covers the following topics - 

1. Introduction to Time Series Forecasting

• What is time series data?
• Applications of forecasting in real life
• Challenges in forecasting

2. Getting Started with Facebook Prophet

• Installing and setting up Prophet
• Importing and preparing datasets
• Understanding Prophet’s framework

3. Core Concepts in Prophet

• Trend modeling
• Seasonality handling (daily, weekly, yearly)
• Adding holiday effects

4. Model Building and Forecasting

• Creating your first forecast
• Plotting and interpreting results
• Handling missing or noisy data

5. Advanced Features in Prophet

• Custom seasonality
• Adding regressors for external factors
• Forecasting with uncertainty intervals

6. Evaluation and Validation

• Measuring accuracy of predictions
• Cross-validation techniques
• Improving forecast quality

7. Real-World Applications

• Business and sales forecasting
• Financial time series predictions
• Demand and supply chain forecasting
• Website traffic and digital analytics

8. Best Practices and Limitations

• When to use Prophet vs other methods
• Avoiding common mistakes
• Scalability and performance considerations