Module 1: Introduction to Python

• Understanding Python and its applications

• Installing Python and setting up the environment

• Python basics: syntax, variables, and data types

• Using Python as a calculator

• Number types: integers, floats, and complex numbers

Module 2: Control Structures

• Mathematical operations in Python

• Working with strings

• Conditional statements (if, elif, else)

• Loops (for, while)

• Functions and modules

Module 3: Errors in Python

• Understanding common errors

• Debugging techniques

• Exception handling

Module 4: Variables

• Variable assignment and data types

• Changing variable types

• Working with multiple variables

Module 5: Strings

• String syntax and escape sequences

• Multi-line strings and string methods

• The input() function

• String indexing, slicing, and comparison

Module 6: Booleans and Conditionals

• Boolean values and logical operations

• Implementing condition-based logic

Module 7: Operators

• Arithmetic, logical, and comparison operators

• Bitwise and identity operators

Module 8: Loops

• Using loops for automation

• The break and continue keywords

Module 9: Python Structures

• Understanding structured programming

• Writing modular and efficient Python code

Module 10: The Power of Lists

• Creating and manipulating lists

• List methods and operations

• Accessing items from lists

Module 11: Data Structures

• Lists and tuples

• Dictionaries and sets

• List comprehensions for optimized code

Module 12: File Handling

• Reading and writing files

• Working with CSV and JSON files

Module 13: Object-Oriented Programming (OOP)

• Understanding classes and objects

• Inheritance and polymorphism

• Exception handling in OOP

Module 14: Web Scraping and APIs

• Introduction to web scraping

• Using BeautifulSoup and Requests library

• Fetching data using APIs

Module 15: Data Analysis with Python

• Introduction to NumPy and Pandas

• Data manipulation and analysis techniques

• Data visualization using Matplotlib

Module 16: Advanced Topics

• Working with databases (SQLite)

• Introduction to Django/Flask for web development

• Basics of machine learning using Scikit-Learn

Projects

• Project 1: Number Guessing Game using Python

• Project 2: URL Shortener using Python

• Project 3: Speech Recognition-based Project

• Project 4: Salary Prediction using Linear Regression

• Project 5: Heart Disease Prediction using Logistic Regression

• Project 6: House Price Prediction using Machine Learning

This structured approach ensures both theoretical understanding and hands-on experience, making you industry-ready by the end of the course.