Time Series Analysis and Forecasting

This course begins with an introduction to time series forecasting, covering key principles, decomposition techniques, and applications in Python. You’ll explore why time series analysis is crucial, gaining hands-on experience through interactive Python demos.

Next, you'll strengthen your statistical foundations by understanding essential forecasting metrics, regression techniques, and handling missing values and outliers in time series data. Python-based exercises will provide practical exposure to real-world challenges.

You'll code and optimize these models in Python, ensuring higher predictive accuracy. Finally, you'll learn multivariate time series forecasting, where multiple variables improve forecasting power. By the end of this course, you will have the expertise to analyze trends, detect seasonality, handle time series challenges, and implement powerful forecasting models—preparing you for success in data science, analytics, and business intelligence.