Astronomy is one of the oldest sciences, dedicated to exploring the nature, origins, and evolution of celestial objects and the universe as a whole. Observational astronomy, one of the main branches of the field, focuses on collecting and studying data from the sky across the entire electromagnetic spectrum, ranging from radio waves to gamma rays. With the advent of powerful ground-based and space-based telescopes, modern observational astronomy has become increasingly data-intensive, requiring the use of advanced tools, programming, and statistical methods to interpret vast datasets. 

This offline workshop is designed for postgraduate and undergraduate students who wish to build a strong foundation in astronomical data analysis. The workshop provides an introduction to astronomical data analysis and offers students the opportunity to explore datasets independently, along with a brief overview of machine learning (ML) techniques and their growing applications in astronomy.