Description
- Introduction to Python for Data Analytics: Overview of Python basics, libraries, and their role in data analytics.
- Data Manipulation:Using Pandas for data cleaning, transformation, and analysis.
- Data Visualization: Creating insightful visualizations with Matplotlib and Seaborn.
- Statistical Analysis:Applying statistical methods and hypothesis testing using Python.
- Machine Learning Basics: Implementing simple machine learning models with Scikit-learn.
- Practical Projects: Analyzing real-world datasets through hands-on projects.
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