
The Ultimate Guide to Web Scraping
Course Description
Web Scraping in Big Data – Course Overview
This comprehensive course provides a step-by-step guide to web scraping, covering everything from basic concepts to advanced techniques. You will learn how to extract, process, and store data efficiently using Python libraries like Requests, BeautifulSoup, Scrapy, and Selenium. The course emphasizes best practices, scalability, and real-world applications, ensuring hands-on experience in data extraction.
By the end of this course, you will be able to build fully functional web scrapers for projects like e-commerce data collection, news aggregation, and weather data analysis.
Course Modules 1. Introduction to Web Scraping
- Understanding web scraping and its applications.
- Legal and ethical guidelines (robots.txt, avoiding personal data scraping).
- Overview of popular web scraping tools: Requests, BeautifulSoup, Scrapy, Selenium.
2. Web Scraping with BeautifulSoup
- Introduction to BeautifulSoup.
- Installing and importing BeautifulSoup.
- Navigating HTML trees and extracting content.
- Handling tables and hierarchical data.
3. Web Scraping with Scrapy
- Introduction to the Scrapy Framework.
- Writing spiders to crawl websites efficiently.
- Storing and exporting scraped data.
4. Web Scraping with Selenium
- Introduction to Selenium for web scraping.
- Automating browser interactions.
- Setting up Selenium WebDriver.
- Handling CAPTCHA and delays.
5. Handling Data Storage
- Storing scraped data in CSV, JSON, MySQL, and MongoDB.
- Using Pandas for data processing and analysis.
6. Working with the Requests Library
- Making HTTP requests (GET, POST, etc.).
- Setting headers and parameters.
- Handling response content:
- Text, JSON, and binary data.
7. Real-World Projects
- E-commerce product scraping.
- News aggregation and content extraction.
- Weather data collection and analysis.
8. Best Practices and Deployment
- Writing clean and maintainable scraping scripts.
- Debugging and testing scrapers effectively.
- Deploying scrapers on cloud platforms like AWS and GCP.
Learning Resources
Each module includes practical demonstrations and references to high-quality YouTube tutorials to reinforce learning.
Who Should Take This Course?
- Beginners looking to get started with web scraping.
- Data analysts, data scientists, and software developers interested in data extraction.
- Professionals working with large-scale web data collection.
By the end of this course, you will have hands-on experience in web scraping and be ready to apply these skills to various real-world applications.
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Course Curriculum

Yogesh Mandakala
Data AnalystI am a Data Analyst with experience in SQL, Python, and Power BI, specializing in data visualization, web scraping, and building data pipelines. I have worked on Big Data Analytics and e-commerce projects, leveraging my analytical skills to extract insights and drive business decisions.