Learn Web Scraping with Python in ONE Video (BeautifulSoup + Requests) | Day 11 скачать в хорошем качестве

Learn Web Scraping with Python in ONE Video (BeautifulSoup + Requests) | Day 11

Welcome to Day 11 of the Full-Stack AI Developer Course! 🚀 In this Web Scraping Masterclass, we go deep into how AI systems can read live data from the internet. code- https://github.com/SIDDHANTSAXENA2004... You’ll learn how to build your own Python web scraper using requests and BeautifulSoup — from fetching a webpage to extracting clean, structured data. This session lays the foundation for AI-powered data pipelines, RAG systems, and intelligent chatbots that learn from the web. 🔥 What’s Inside: Difference between APIs & Web Scraping Using requests.get() safely Navigating HTML with BeautifulSoup Using find(), find_all(), class_, and id Extracting links, text, and other key info Saving scraped data into .txt files for AI models 💡 Next (Day 12): We’ll connect this scraped data to LangChain + Gemini AI and build a chatbot that knows what’s new on the web. 0:00 – Intro: Why AI needs Web Scraping 1:14 – What is RAG (Retriever Augmented Generation)? 2:44 – Example: Scraping Wikipedia 4:09 – Installing requests & beautifulsoup4 5:30 – Understanding requests.get() & headers 6:47 – What is BeautifulSoup and how it works 7:47 – find() vs find_all() explained 10:23 – Adding headers to avoid blocks 12:48 – HTTP Status Codes (200, 403, 404) 14:47 – Creating the soup object 15:31 – Extracting the page title 20:00 – Extracting all paragraphs 24:14 – .find() vs .find_all() difference 26:07 – Using id to target specific sections 32:20 – Using class_ to extract grouped data 37:13 – Extracting hyperlinks using .get('href') 39:06 – Final: Scraping all reference links 40:00 – Saving scraped data to scraped_knowledge.txt 41:00 – Recap & Day 12 Preview (LangChain + RAG) #Python #AI #WebScraping #BeautifulSoup #Requests #DataScience #FullStackAI #MachineLearning #LangChain #RAG #GeminiAI #LearnToCode #AIDevelopment #CodingTutorial #PythonForAI