Course Overview

Overview

The course is divided into four sections, each focusing on a specific aspect of web scraping. In this course, we will cover the following topics:

• The overview of web scraping and the primary elements of websites.

• The fundamental concepts of web scraping such as HTTP requests, parsing HTML documents, and extracting data from web pages.

• Advanced web scraping techniques, such as dynamic web pages that use JavaScript to update content. We’ll learn how to use libraries like Selenium and Splash to scrape dynamic websites.

• Building large-scale web scraping projects using Scrapy, a Python-based framework. We’ll learn how to structure a web scraping project, scale to a large number of websites, and handle errors and exceptions.

Who this course is for

This course is intended for:

• Learners who have a basic familiarity with Python programming concepts and syntax.

• Beginners who have little to no experience with web scraping.

• Experienced Python programmers who want to learn how to scrape website data.

Prerequisites

To take this course, you should have:

• A basic understanding of Python programming concepts and syntax

• Understand control flow statements, variables, data types, and basic data structures

• Some familiarity with HTML and CSS would also be helpful, but it is unnecessary

Learning outcomes

By the end of this course, you’ll be able to:

• Understand the main web scraping concepts and elements, including HTTP requests, HTML, CSS, and JavaScript.

• Use Python libraries such as Requests, Beautiful Soup, and Selenium to scrape website data.

• Scrape data from static and dynamic websites, including websites that require JavaScript rendering.

• Store and analyze scraped data using Python libraries such as pandas and NumPy.

• Build large-scale scraping projects using Scrapy and Scale to scrape many websites.

• Write clean, efficient, and robust code for web scraping projects.

After completing the course, you will have the skills and knowledge to scrape data from various websites for personal and professional use. You can automate data collection processes and use the scraped data to gain insights, make data-driven decisions, and build data-driven applications.