Module 1: Introduction to Python

• Overview of Python and its real-world applications
• Python features, advantages, and use cases
• Installing Python and setting up the development environment
• Running Python programs (interactive mode vs script mode)

Module 2: Python Basics

• Python syntax and code structure
• Variables and data types
• Type casting and input/output operations
• Basic operators (arithmetic, comparison, logical)

Module 3: Control Flow Statements

• Conditional statements (if, elif, else)
• Looping constructs (for, while)
• Loop control (break, continue, pass)
• Nested loops and logical flow design

Module 4: Data Structures in Python

• Lists: creation, indexing, slicing, methods
• Tuples and immutability
• Sets and set operations
• Dictionaries and key-value handling
• Practical data manipulation examples

Module 5: Functions and Recursion

• Defining and calling functions
• Function arguments and return values
• Default and keyword arguments
• Recursive functions and use cases
• Scope of variables (local vs global)

Module 6: Object-Oriented Programming

• OOP concepts: class, object, methods
• Constructors and instance variables
• Inheritance and polymorphism
• Encapsulation and abstraction
• Real-world OOP examples in Python

Module 7: Exception Handling

• Understanding runtime errors
• Using try, except, else, and finally
• Handling multiple exceptions
• Creating custom exceptions
• Best practices for error handling

Module 8: File Handling

• Reading and writing text files
• File modes and file pointers
• Working with CSV and basic data files
• Context management
• File handling best practices

Module 9: Modules and Packages

• Importing built-in modules
• Creating user-defined modules
• Using external packages with pip
• Understanding package structure
• Virtual environment basics

Module 10: Python for Automation / Scripting

• Automating repetitive tasks
• File and folder automation
• Working with OS and system commands
• Basic web automation concepts
• Real-world scripting use cases

Module 11: Working with Databases (SQL)

• Database fundamentals
• Connecting Python with SQL databases
• Performing CRUD operations
• Executing SQL queries using Python
• Handling database exceptions

Module 12: Regular Expressions

• Pattern matching concepts
• Searching, matching, and replacing text
• Common regex patterns
• Practical text-processing examples

Module 13: GUI Programming with Tkinter

• Introduction to GUI development
• Creating windows, buttons, labels, and input fields
• Event handling
• Layout management
• Building simple desktop applications

Module 14: Introduction to Data Analysis with Python

• Basics of data analysis workflow
• Working with arrays and data frames
• Data cleaning and transformation
• Basic data visualization concepts
• Introduction to popular data libraries

Module 15: Introduction to Machine Learning

• What is Machine Learning, and its types
• ML workflow and terminology
• Data preparation for ML
• Implementing simple ML models
• Model evaluation basics

Module 16: Testing and Debugging

• Debugging techniques in Python
• Using debugging tools and logs
• Writing unit tests
• Understanding common bugs
• Improving code reliability

Module 17: Project

• End-to-end Python project development
• Requirement analysis and planning
• Coding, testing, and optimization
• Real-world problem solving
• Project presentation and documentation

Exam Preparation

• Python syntax and concept revision
• Practice questions and mock tests
• Problem-solving strategies
• Time management tips

Interview Preparation

• Common Python interview questions
• Coding exercises and logic building
• OOP and data structure questions
• Resume-oriented project discussion
• Technical and HR interview tips