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| File Name: | Data Analysis Using Python: Practical Skills and Projects |
| Content Source: | https://www.udemy.com/course/data-analysis-using-python-practical-skills-and-projects/ |
| Genre / Category: | Programming |
| File Size : | 4.7 GB |
| Publisher: | udemy |
| Updated and Published: | May 19, 2024 |
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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