Introduction to python and python for data analysis libraries

Learning Objectives

1. Introduction to data analysis: What is data analysis? Why is it important? what are its applications?
2. Setting up your Python environment.
3. Installing Python and Jupyter Notebook.
4. Introduction to Python basics: Data types, variables, operators, expressions, control flow.
5. Working with data in Python: Importing data from CSV files, exploring and cleaning data.
6. Data visualization with Python: Matplotlib and Seaborn for creating charts and graphs.

Project: Analyze a personal datasets (e.g., your music library, spending habits, fitness tracker data) and create visualizations to tell a story about it.