Description:

Time Series Foundation is an in-depth course that covers the fundamental concepts, techniques, and applications of time series analysis. The course provides a comprehensive understanding of time series data, statistical models, forecasting methods, and advanced analytics tools used in analyzing time-dependent data. Participants will learn how to identify patterns, trends, and seasonality in time series data, as well as how to build predictive models and make informed decisions based on time series analysis.

Key Highlights:

• Fundamental concepts of time series analysis
• Statistical models and forecasting techniques
• Hands-on experience with time series data
• Practical applications and case studies

What you will learn:

• Understand Time Series Data
  Explore the key components of time series data and how to preprocess and visualize it for analysis.
• Statistical Models for Time Series
  Learn about popular statistical models like ARIMA, SARIMA, and exponential smoothing for time series forecasting.
• Forecasting Methods
  Discover various techniques for forecasting future values in time series data, including trend analysis and seasonal decomposition.