Data Analysis Using Python: Practical Skills and Projects

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This course provides a comprehensive introduction to data analysis using Python. It covers essential libraries like NumPy and pandas, and explores data visualization with Plotly. The course culminates in an end-to-end project analyzing the Google Playstore dataset, providing practical experience in applying the learned techniques to real-world data.

Modules and Key Features:

Module 1: Introduction to Data Analysis with Python

• Overview of data analysis and its importance
• Introduction to the concept and significance of data analysis in various fields.
• Understanding the benefits of data-driven decision making.
• Introduction to Python for data analysis course content

Module 2: Introduction to NumPy

• Introduction to NumPy arrays
• Understanding the structure and benefits of NumPy arrays over Python lists.
• Creat ing NumPy arrays from lists and using built-in functions.
• Basic array operations (creation, manipulation)
• Performing fundamental array operations such as reshaping, slicing, and element-wise operations.
• Array indexing and slicing
• Mastering techniques to access and modify specific parts of an array.
• Universal functions (ufuncs)
• Utilizing universal functions for element-wise operations and mathematical computations.
• Array broadcasting
• Understanding the concept of broadcasting and how it enables operations on arrays of different shapes.
• Mathematical functions
• Using built-in mathematical functions to perform calculations on arrays.

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