The Web Scraping with Python Certified Course is designed to equip learners with the skills to extract, process, and analyze data from websites efficiently using Python. Through this hands-on program, you’ll learn how to collect real-time data from dynamic web pages, automate data collection tasks, and convert unstructured web data into meaningful insights. The course covers key Python libraries like BeautifulSoup, Requests, Selenium, and Scrapy, enabling you to handle both static and JavaScript-driven websites. Whether you aim to build data-driven applications, monitor market trends, or support machine learning models with real-world data, this course provides the essential knowledge and practical experience to master web data extraction like a professional.
Module 1: Introduction to Web Scraping & Python Refresher Overview of web scraping and its applications Setting up Python environment (Anaconda, PyCharm, VS Code) Python fundamentals review for scraping: loops, functions, and data types
Module 2: HTML, CSS, and Web Page Structure Understanding HTML tags, attributes, and page hierarchy CSS selectors and XPath basics Using Chrome DevTools and Firefox Developer Tools to inspect web pages.
Module 3: HTTP Requests and Web Page Interaction Introduction to HTTP, URLs, and web protocols Using Python Requests library to fetch web content Handling headers, cookies, and sessions.
Module 4: Parsing Web Data with BeautifulSoup Navigating and searching the parse tree Extracting text, links, tables, and images Handling dynamic and nested HTML structures.
Module 5: Automating Browsers with Selenium Introduction to Selenium and browser drivers Interacting with dynamic web pages Handling forms, buttons, and JavaScript content.
Module 6: Advanced Scraping with Scrapy Framework Setting up Scrapy projects Writing spiders to crawl websites efficiently Pipelines, item loaders, and exporting data.
Module 7: Data Cleaning and Storage Working with Pandas and NumPy for data cleaning Handling missing, duplicate, and inconsistent data Storing scraped data in CSV, JSON, SQLite, MySQL, or MongoDB.
Module 8: Working with APIs and JSON Data Understanding REST APIs and endpoints Fetching and parsing JSON responses Integrating API data with scraped data.
Module 9: Automation, Scheduling, and Error Handling Writing reusable and robust scraping scripts Using logging, exception handling, and debugging techniques Automating scripts with Task Scheduler or Cron Jobs.
Module 10: Real-World Projects & Case Studies Hands-on projects: e-commerce scraping, market research, social media data extraction Building complete end-to-end scraping pipelines Ethical web scraping practices and legal considerations.
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Email: coursedivine@gmail.com
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