Python OOP tutorial, Python Classes, Python Objects, Python Constructor, Python *init* Method, Python self Parameter, Python Class Properties, and Python Class Methods explained for beginners. Learn Python OOP from scratch with live coding, real-world examples, and hands-on practice.
🔥 Python Developer Series #5 | Phase 2: Intermediate Python
In today's LIVE session, you'll learn Object-Oriented Programming (OOP) in Python by building classes and objects from scratch. We'll understand the Python constructor (`__init__`), the `self` parameter, class properties, class methods, and solve a coding challenge to strengthen your understanding.
📚 Today's Topics
✅ Introduction to Python OOP
✅ Python Classes
✅ Python Objects
✅ Python Constructor (`__init__`)
✅ Python self Parameter
✅ Python Class Properties
✅ Python Class Methods
✅ Live Coding
✅ Code Challenge
✅ Real-Time Doubt Solving
📌 Chapters
00:00 Python OOP Introduction
03:11 Python OOP Roadmap
07:38 Python Classes
13:58 Python Objects
25:23 Python Constructor (**init**)
43:02 Python self Parameter
57:41 CODE WITH NM Family & Discord
01:01:51 CODE WITH NM Website & Python Quizzes
01:04:38 Python Class Properties
01:30:58 Session Wrap-up
📅 Date: 27 June 2026 (Saturday)
⏰ Time: 8:00 PM IST
📚 Playlist:
Python Developer Bootcamp | Live Learning with CODE WITH NM
🚀 Phase 2 Roadmap
✅ File Handling
✅ Error Handling
✅ Modules & Packages
✅ Python OOP
🔜 Python Inheritance
🔜 Python Polymorphism
🔜 Python Encapsulation
🔜 JSON
🔜 APIs
🔜 Weather App Project
━━━━━━━━━━━━━━━━━━━━
👨💻 About CODE WITH NM
Welcome to CODE WITH NM — a live-learning platform founded by Nilesh Maurya, helping students and professionals become industry-ready through structured roadmaps, real-world projects, and community-driven learning.
🌟 Join the CODE WITH NM Family:
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Inside Discord:
✅ Session Notes
✅ Doubt Corner
✅ Code Sharing
✅ Learning Resources
✅ Weekly Challenges
✅ Community Support
👨💻 Founder:
Nilesh Maurya
🌐 Website:
https://codewithnm.com
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https://github.com/codewithnm
🚀 Learning Roadmap
Python Developer → Data Analyst → Data Science → Machine Learning → AI → LLM Applications
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