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LoginModule 3 begins
Duration: 0.1 Months
Learn Python, Numpy, and Pandas libraries for analysis.
- Core Python fundamentals, including variables, data types, loops, conditionals, and functions.
- Practical experience using the Date Time, Numpy, and Pandas libraries for analysis.
- Data Cleaning: Missing data, outliers.
- Techniques for handling missing data and outliers, followed by creating visual insights with Matplotlib and Seaborn.
Module concludes
In this module, students will master Python programming for data analytics. They’ll build a strong foundation in core syntax, variables, and functions before diving into powerful libraries like NumPy and Pandas for high-performance data manipulation. This module emphasises practical data cleaning—addressing missing values and outliers—and concludes with transforming raw datasets into compelling visual stories using Matplotlib and Seaborn, equipping students with the essential coding skills for advanced analytical workflows.
