Module 1: Introduction to Python and Setup
- Introduction to Python: Relevance and Applications
- Setting up Python Environment
- Writing and Executing Python Scripts
- Python Syntax, Comments, and Indentation
Module 2: Python Basics
- Variables and Data Types
- Input and Output Operations
- Operators: Arithmetic, Assignment, Comparison, Logical, Bitwise
- Basic Control Flow Statements
Module 3: Data Structures
- Lists: Creation, Indexing, Slicing, and Modifying
- Tuples: Properties and Use Cases
- Sets: Union, Intersection, and Difference
- Dictionaries: Key-Value Pairs and Operations
Module 4: Functions and Modules
- Defining and Calling Functions
- Parameters, Return Values, and Arguments
- Lambda Functions and Scope
- Python Modules and Packages
- Creating Custom Modules
Module 5: File Handling
- File Operations: Reading, Writing, and Appending
- File Modes
- Exception Handling
Module 6: Object-Oriented Programming (OOP)
- Classes and Objects
- __init__ Constructor
- Inheritance and Polymorphism
- Encapsulation and Abstraction
Module 7: Python Libraries and Advanced Topics
- Libraries: numpy, pandas, matplotlib
- Regular Expressions
- Iterators and Generators
- Decorators
Module 8: Working with APIs and Web Scraping
- APIs: REST APIs and HTTP Requests
- Web Scraping: BeautifulSoup and selenium
Module 9: Introduction to Data Science with Python
- Data Analysis with pandas
- Data Visualization with matplotlib and seaborn
- Basic Machine Learning with scikit-learn
Module 10: Capstone Project and Revision
- Capstone Project
- Debugging and Error Handling
- Revision and Final Assessment