Python Programming is a modern and beginner-friendly programming course designed to build strong coding and problem-solving skills. This course covers Python syntax, data types, loops, functions, lists, dictionaries, file handling, and modules, along with an introduction to Object-Oriented Programming and basic data analysis.
Python is widely used in web development, data science, AI, automation, and app development, making this course ideal for students who want to start a career in technology or software development.
Module 1: Introduction to Python: What is Python? History and Applications, Installing Python & IDEs (IDLE, VS Code, Jupyter), Python Shell vs Script Mode, First Python Program (Hello World), Comments and Basic Syntax, Data Types and Variables, Input/Output Functions, Type Casting.
Module 2: Operators and Expressions: Arithmetic, Comparison, Logical Operators, Assignment Operators, Bitwise, Membership & Identity Operators, Operator Precedence.
Module 3: Control Flow: Conditional Statements: if, elfin, else, Loops: for, while, Loop Control Statements: break, continue, pass, Nested Loops.
Module 4: Data Structures: Strings, Lists and List Comprehension, Tuples, Dictionaries, Sets, Built-in Functions for Data Structures.
Module 5: Functions and Modules: Defining Functions, Arguments & Return Values, Lambda Functions, Variable Scope (local, global), Importing and Creating Modules, Built-in Modules (math, datetime, random, etc.)
Module 6: File Handling: Opening, Reading, Writing, and Closing Files, Working with Text and Binary Files, File Methods and Context Manager (with statement).
Module 7: Exception Handling: Errors and Exceptions, try, except, else, finally, Custom Exception Handling.
Module 8: Object-Oriented Programming (OOP): Classes and Objects, __init__ Constructor, Attributes and Methods, Inheritance, Encapsulation and Polymorphism, super() and Method Overriding.
Module 9: Working with Libraries: requests (HTTP Requests), json (Working with JSON), os, sys, time, re, pandas and numpy (Introduction for data handling).
Module 10: Projects & Practice: Mini Projects (e.g., Calculator, To-do app, Quiz game), Capstone Project: Choose from Web Scraping, Data Analysis, CLI App, etc., Best Practices & Code Reviews.
Optional Advanced Topics: Virtual Environments (venv, pip), Working with APIs, Unit Testing (unittest, pytest), Introduction to GUI with tkinter, Introduction to Web Development using Flask or Django.
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