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Web Scraping with Python

  • Course Code: Data Analysis / BI - Web Scraping with Python
  • Course Dates: Contact us to schedule.
  • Course Category: Big Data & Data Science Duration: 3 Days Audience: This course is geared for those who wants to Collect and scrape different complexities of data from the modern Web using the latest tools, best practices, and techniques

Course Snapshot 

  • Duration: 3 days 
  • Skill-level: Foundation level Web Scraping with Python skills for Intermediate skilled team members. This is not a basic class. 
  • Targeted Audience: This course is geared for those who wants to Collect and scrape different complexities of data from the modern Web using the latest tools, best practices, and techniques 
  • Hands-on Learning: This course is approximately 50% hands-on lab to 50% lecture ratio, combining engaging lecture, demos, group activities and discussions with machine-based student labs and exercises. Student machines are required. 
  • Delivery Format: This course is available for onsite private classroom presentation, or remote instructor led delivery, or CBT/WBT (by request). 
  • Customizable: This course may be tailored to target your specific training skills objectives, tools of choice and learning goals. 

Web scraping is an essential technique used in many organizations to gather valuable data from web pages. This course will enable you to delve into web scraping techniques and methodologies. The course will introduce you to the fundamental concepts of web scraping techniques and how they can be applied to multiple sets of web pages. You’ll use powerful libraries from the Python ecosystem such as Scrapy, lxml, pyquery, and bs4 to carry out web scraping operations. You will then get up to speed with simple to intermediate scraping operations such as identifying information from web pages and using patterns or attributes to retrieve information. This course adopts a practical approach to web scraping concepts and tools, guiding you through a series of use cases and showing you how to use the best tools and techniques to efficiently scrape web pages. You’ll even cover the use of other popular web scraping tools, such as Selenium, Regex, and web-based APIs. By the end of this course, you will have learned how to efficiently scrape the web using different techniques with Python and other popular tools. 

Working in a hands-on learning environment, led by our Web Scraping with Python expert instructor, students will learn about and explore: 

  • Learn different scraping techniques using a range of Python libraries such as Scrapy and Beautiful Soup 
  • Build scrapers and crawlers to extract relevant information from the web 
  • Automate web scraping operations to bridge the accuracy gap and manage complex business needs 

Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below 

  • Analyze data and information from web pages 
  • Learn how to use browser-based developer tools from the scraping perspective 
  • Use XPath and CSS selectors to identify and explore markup elements 
  • Learn to handle and manage cookies 
  • Explore advanced concepts in handling HTML forms and processing logins 
  • Optimize web securities, data storage, and API use to scrape data 
  • Use Regex with Python to extract data 
  • Deal with complex web entities by using Selenium to find and extract data 

Audience & Pre-Requisites 

This course is written for Readers wants to Collect and scrape different complexities of data from the modern Web using the latest tools, best practices, and techniques.  

Pre-Requisites:  Students should have  

Basic IT and Python knowledge and skills 

Course Agenda / Topics 

  1. Web Scraping Fundamentals 
  • Web Scraping Fundamentals 
  • Introduction to web scraping 
  • Understanding web development and technologies 
  • Data finding techniques for the web 
  • Python and the Web – Using urllib and Requests 
  • Python and the Web – Using urllib and Requests 
  • Technical requirements 
  • Accessing the web with Python 
  • URL handling and operations with urllib and requests 
  • Implementing HTTP methods 
  1. Using LXML, XPath, and CSS Selectors 
  • Using LXML, XPath, and CSS Selectors 
  • Technical requirements 
  • Introduction to XPath and CSS selector 
  • Using web browser developer tools for accessing web content 
  • Scraping using lxml, a Python library 
  1. Scraping Using pyquery – a Python Library 
  • Scraping Using pyquery – a Python Library 
  • Technical requirements 
  • Introduction to pyquery 
  • Exploring pyquery 
  • Web scraping using pyquery 
  1. Web Scraping Using Scrapy and Beautiful Soup 
  • Web Scraping Using Scrapy and Beautiful Soup 
  • Technical requirements 
  • Web scraping using Beautiful Soup 
  • Web scraping using Scrapy 
  • Deploying a web crawler 
  1. Working with Secure Web 
  • Working with Secure Web 
  • Technical requirements 
  • Introduction to secure web 
  • HTML <form> processing 
  • Handling user authentication 
  • Working with cookies and sessions 
  1. Data Extraction Using Web-Based APIs 
  • Data Extraction Using Web-Based APIs 
  • Technical requirements 
  • Introduction to web APIs 
  • Accessing web API and data formats 
  • Web scraping using APIs 
  1. Using Selenium to Scrape the Web 
  • Using Selenium to Scrape the Web 
  • Technical requirements 
  • Introduction to Selenium 
  • Using Selenium for web scraping 
  1. Using Regex to Extract Data 
  • Using Regex to Extract Data 
  • Technical requirements 
  • Overview of regular expressions 
  • Using regular expressions to extract data 
  1. Next Steps 
  • Next Steps 
  • Technical requirements 
  • Managing scraped data 
  • Analysis and visualization using pandas and matplotlib 
  • Machine learning  
  • Data mining 
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