Section outline

• Select section Day 1: Introduction to Data Scraping

  Day 1: Introduction to Data Scraping

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  • Introduction to Data Scraping (1 Hour)
    • Overview, applications, and ethical considerations.
  • Web Scraping Basics (3 Hours)
    • Understanding HTML, DOM, and web page structures.
    • Tools and libraries for web scraping.
  • Beautiful Soup for Web Scraping (3 Hours)
    • Navigating and parsing HTML.
    • Hands-on exercises extracting data using tags and attributes.
• Select section Day 2: Advanced Web Scraping Techniques

  Day 2: Advanced Web Scraping Techniques

  • Scrapy for Large-Scale Scraping (3 Hours)
    • Setting up Scrapy projects, handling pagination, and complex extractions.
  • Selenium for Dynamic Content (2 Hours)
    • Automating browsers for JavaScript-rendered content.
    • Interaction with dynamic elements like forms and buttons.
  • Data Cleaning and Preparation (2 Hours)
    • Techniques for handling missing data and duplicates using Pandas.
• Select section Day 3: Introduction to Data Mining

  Day 3: Introduction to Data Mining

  • Introduction to Data Mining (1 Hour)
    • Overview of concepts, tasks, and applications.
  • Clustering and Classification (3 Hours)
    • Techniques like K-means and decision trees.
    • Implementation using Scikit-learn.
  • Association Rules and Pattern Mining (2 Hours)
    • Market basket analysis and Apriori algorithm.
  • Project and Case Study (2 Hours)
    • End-to-end data scraping and mining workflow.
    • Presenting findings and insights from practical projects.