Web scraping with ChatGPT

Web Scraping with ChatGPT is a specialized course designed to teach students how to combine web scraping techniques with ChatGPT, a language model AI, to extract and process data from the web. This course provides a deep understanding of web scraping, data extraction, and how to use ChatGPT for further analysis, generation, and interpretation of web data.

Course Objectives:
  1. Web Scraping Fundamentals: Gain a comprehensive understanding of web scraping techniques, including HTML parsing, HTTP requests, and using libraries like Beautiful Soup and Scrapy.
  2. ChatGPT Integration: Learn how to incorporate ChatGPT or similar language models to process and analyze the scraped data for various applications.
  3. Data Processing: Master data cleaning, transformation, and storage techniques to prepare scraped data for analysis and use with ChatGPT.
  4. Interactive Data Interpretation: Explore how ChatGPT can be used to generate insights, summaries, and natural language responses from the scraped data.
  5. Automated Data Collection: Create web scraping pipelines that automatically collect and analyze data from websites on a regular basis.
  6. Ethical Considerations: Discuss ethical considerations in web scraping, including terms of service, responsible data usage, and legal compliance.
  7. Real-World Projects: Apply your skills through hands-on projects, such as creating news summarization systems, price monitoring tools, or data-driven chatbots.

Course Prerequisites:
  • Basic Programming Knowledge
  • Web Basics
  • AI Fundamentals

Target Audience:

 This course is suitable for individuals with a variety of backgrounds and interests, including:
  • Data Scientists and Analysts
  • Developers and Engineers
  • Business Analysts
  • Researchers and Academics.
  • Entrepreneurs and Startups
  • AI Enthusiasts

By the end of this course, participants will have the skills and knowledge required to extract, process, and analyze data from the web using web scraping techniques and integrate ChatGPT for interactive data interpretation and natural language responses.

Course Summary

Course Fee

৳ 10,000

Training Method

Offline/Online

Total Modules

5

Course Duration

24 Hours

Total Session

12

Class Duration

2 Hours

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Details Course Outlines - Web scraping with ChatGPT

Module-01

Introduction to Web Scraping and ChatGPT

  • Session 1: Getting Started
  • 1.1.1 Introduction to Web Scraping
  • Overview of web scraping and its applications.
  • The importance of data extraction from websites.
  • Understanding ethical considerations and legal aspects.
  • 1.1.2 Tools and Libraries for Web Scraping
  • Introduction to key tools and libraries for web scraping (e.g., Python, BeautifulSoup, Requests).
  • Setting up your development environment (Python installation and package management).
  • Basic HTML and CSS overview to understand web page structure.
  • Session 2: Python Fundamentals
  • 1.2.1 Introduction to Python for Web Scraping
  • Basics of Python programming language.
  • Key concepts such as variables, data types, and operators.
  • Writing your first Python script for web scraping.
  • 1.2.2 Web Requests with Python
  • How to make HTTP requests using Python's Requests library.
  • Understanding HTTP methods (GET, POST, etc.).
  • Handling HTTP responses and status codes (e.g., 200 OK, 404 Not Found).
  • Session 3: Introduction to ChatGPT for Web Scraping
  • 1.3.1 Introduction to ChatGPT
  • Overview of ChatGPT and its capabilities
  • Use cases for ChatGPT in web scraping
  • Accessing the ChatGPT API and authentication.
  • 1.3.2 Getting Started with ChatGPT for Web Scraping
  • Practical demonstration of using ChatGPT for web scraping tasks.
  • Extracting structured data from web pages using ChatGPT.
  • Examples of using ChatGPT for text extraction and analysis from websites.

Module-02

Advanced Web Scraping Techniques with ChatGPT

  • Session 1: ChatGPT for Text Extraction and Analysis
  • 2.1.1 Text Extraction with ChatGPT
  • Expanding on text extraction techniques using ChatGPT.
  • Strategies for extracting text content from various web page elements.
  • Examples of using ChatGPT for extracting and cleaning text data.
  • 2.1.2 Text Analysis with ChatGPT
  • Introduction to text analysis tasks with ChatGPT
  • Summarizing text content using ChatGPT.
  • Building a simple keyword extractor with ChatGPT.
  • Session 2: Handling Complex Data
  • 2.2.1 Extracting Data from Tables and Lists
  • Techniques for extracting structured data from tables and lists on web pages.
  • Overview of HTML parsing and traversal.
  • Practical exercises on extracting tabular data with ChatGPT.
  • 2.2.2 Combining ChatGPT and BeautifulSoup
  • How to combine the capabilities of ChatGPT and BeautifulSoup for advanced data extraction.
  • Extracting data from complex web page structures.
  • Case study: Extracting data from a dynamic website using ChatGPT and BeautifulSoup.
  • Session 3: Best Practices and Ethical Considerations
  • 2.3.2 Error Handling and Optimization
  • Techniques for handling errors and exceptions in web scraping scripts.
  • Debugging and troubleshooting common issues.
  • Scalability and optimization of web scraping scripts for efficiency.

Module-03

Selenium for Web Scraping

  • Session 1: Introduction to Selenium
  • 3.1.1 Basic concept of Selenium
  • Overview of Selenium as a web automation tool.
  • Use cases and advantages of using Selenium for web scraping.
  • Installing Selenium and configuring WebDriver for different browsers.
  • 3.1.2 Navigating Websites with Selenium
  • Practical demonstration of navigating websites using Selenium.
  • Opening and closing web browser windows.
  • Navigating through web pages, including back and forward navigation.
  • Session 2: Advanced Selenium Techniques
  • 3.2.1 Handling Dynamic Web Pages
  • Understanding dynamic web pages and their challenges in web scraping.
  • Techniques for handling JavaScript-rendered content with Selenium.
  • Case study: Scraping data from a dynamically loaded web page.
  • 3.2.2 Synchronizing Web Element Interactions
  • Exploring synchronization strategies to ensure web elements are ready for interaction.
  • Waiting for page elements to load using explicit and implicit waits.
  • Handling AJAX requests and delays.
  • Session 3: Data Extraction and Automation
  • 3.3.1 Extracting Data from Web Elements
  • Techniques for extracting data from various web elements (e.g., text, images, links).
  • Interacting with forms, input fields, and buttons using Selenium.
  • Extracting and manipulating data from HTML forms.
  • 3.3.2 Automating Web Scraping Tasks with Selenium
  • Designing and implementing automation scripts for web scraping tasks.
  • Combining Selenium with ChatGPT for enhanced data extraction and interaction.
  • Building practical web scraping automation examples.

Module-04

Real-World Projects and Case Studies

  • Session 1: Building Practical Projects
  • 4.1.1 Define a Web Scraping Project
  • Discuss various web scraping project ideas and their real-world applications.
  • Guidelines for defining the scope, objectives, and requirements of a web scraping project.
  • Assistance in selecting a project or refining project ideas.
  • 4.1.2 Designing the Project Structure and Data Storage
  • Planning the project's structure and organization.
  • Choosing the appropriate data storage methods (e.g., CSV, JSON, databases).
  • Designing the database schema if applicable.
  • 4.2.1 Guidance and Assistance on Project Work
  • Dedicated time for students to work on their chosen web scraping projects.
  • Instructor support and guidance for overcoming project-related challenges.
  • Reviewing and providing feedback on project progress.
  • 4.2.2 Addressing Common Issues and Challenges
  • Troubleshooting common issues faced during web scraping projects.
  • Strategies for handling unexpected situations and errors.
  • Best practices for debugging and refining web scraping code.

Module-05

Final Assessment and Certification

  • Final Assessment Exam
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