Forecasting

Forecasting is the process of making predictions about future events or trends based on historical data, statistical models, and domain knowledge. It involves analyzing patterns, identifying relationships, and using techniques like time series analysis, regression, or machine learning to estimate future outcomes. This concept is widely applied in fields such as finance, supply chain management, weather prediction, and business planning to support decision-making and risk assessment.

Also known as: Prediction, Time series forecasting, Trend analysis, Prognostication, Estimation

Why learn Forecasting?

Developers should learn forecasting to build data-driven applications that predict trends, optimize resources, or automate decision processes, such as in demand forecasting for e-commerce, stock price prediction in fintech, or anomaly detection in system monitoring. It is essential for roles involving data science, analytics, or systems that require proactive adjustments based on anticipated changes, helping reduce uncertainty and improve efficiency in dynamic environments.

Learning Resources

• book: Forecasting: Principles and Practice
• tutorial: Time Series Forecasting with Python
• course: Forecasting in R
• course: Introduction to Forecasting
• docs: Forecasting Documentation by Statsmodels