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.