Advanced Python

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Python Tools for Data Analytics
Chapter 1: Introduction to Python Programming
Chapter 2: Control Flow and Looping in Python
Chapter 3: Functions and Functional Programming
Chapter 4: Data Structures and Variables in Python
Chapter 5: Object-Oriented Programming (OOP)
Chapter 6: Decorators and Generators
Chapter 7: Modules and Packages
Chapter 8: File Handling
Chapter 9: Error and Exception Handling
Chapter 10: Working with Libraries
Chapter 11: Database Operations and Data Serialization
Chapter 12: NumPy for Data Analysis
Chapter 13: Pandas for Data Analysis
Chapter 14: Data Visualization with Matplotlib and Seaborn
Chapter 15: Understanding Exploratory Data Analysis (EDA) Frameworks
Chapter 16:
Mini Project 1
Mini Project 2

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Chapter 15: Understanding Exploratory Data Analysis (EDA) Frameworks

3. CRISP-DM (Cross-Industry Standard Process for Data Mining)

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