This comprehensive course will equip you with the essential skills to analyze, model, and forecast time-series data effectively. Whether you’re a data scientist, analyst, or business professional seeking to extract valuable insights from time-dependent data, this course will empower you to make informed decisions.
Delve into the world of time series analysis as we explore fundamental concepts, practical techniques, and advanced modelling approaches. You’ll learn to handle various time series patterns, including trends, seasonality, and cyclicality, and understand how to transform non-stationary data into a suitable format for analysis.
Discover the art of time series visualization to uncover hidden patterns and trends. Master Python libraries like Pandas, NumPy, and Matplotlib for efficient data manipulation and exploration. Gain hands-on experience with real-world datasets to solidify your understanding and build a strong foundation in time series analysis.
Unleash the predictive power of time series forecasting. Learn to build and evaluate different forecasting models, including ARIMA, SARIMA, and exponential smoothing. Discover how to select the most appropriate model for your specific dataset and refine your forecasts for optimal accuracy.
Course Content
Section 1: Foundations of Time Series Analysis
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Introduction to Time Series Data
10:01 -
Understanding Time Series Components
12:38 -
Stationarity and Its Importance
08:07