Cleaning & Analysis with Pandas is designed for students and aspiring data analysts who want to learn how to prepare, clean, and analyze data efficiently using Python. This session introduces the fundamentals of data cleaning and data analysis, focusing on how Pandas, one of the most powerful and widely used Python libraries, can be utilized to process real-world datasets.

Participants will learn how to handle missing values, correct inconsistent data, filter and transform datasets, and perform basic to intermediate data analysis. The session also covers essential Pandas functions for data exploration, aggregation, and summary statistics to help participants uncover meaningful insights from raw data. Through guided explanations and hands-on practice, attendees will gain practical experience in working with structured data effectively.

By the end of the class, participants will have a solid understanding of data cleaning and analysis principles, be able to use Pandas to process and analyze datasets, and feel more confident in turning raw data into reliable insights that support better analysis and data-driven decision-making.