Web Scraping Projects for Beginners

Web Scraping Projects for Beginners

Web Scraping Projects for Beginners

Extract data with Python , JavaScript, API and using No Code

Language: english

Note: 0/5 (0 notes) 308 students  New course 

Instructor(s): Bluelime Learning Solutions

Last update: 2022-06-28

What you’ll learn

  • Scrape data automatically with No Code
  • Scrape YouTube data using JavaScript and YouTube Data API
  • Scrape Amazon Data with Python
  • Scrape data with Scrapy
  • Scrape data with BeautifuSoup
  • Scrape data into GoogleSheets from YouTube

 

Requirements

  • Basic knowledge of Python advised
  • Basic knowledge of JavaScript advised.

 

Description

Web scraping is the process of collecting structured web data in an automated fashion. It’s also called web data extraction. Some of the main use cases of web scraping include price monitoring, price intelligence, news monitoring, lead generation, and market research among many others.


In general, web data extraction is used by people and businesses who want to make use of the vast amount of publicly available web data to make smarter decisions.


If you’ve ever copied and pasted information from a website, you’ve performed the same function as any web scraper, only on a microscopic, manual scale. Unlike the mundane, mind-numbing process of manually extracting data, web scraping uses intelligent automation to retrieve hundreds, millions, or even billions of data points from the internet’s seemingly endless frontier.

Web data extraction – also widely known as data scraping – has a huge range of applications. A data scraping tool can help you automate the process of extracting information from other websites, quickly and accurately. It can also make sure the data you’ve extracted is neatly organized, making it easier to analyze and use for other projects.

In the world of e-commerce, web data scraping is widely used for competitor price monitoring. It’s the only practical way for brands to check the pricing of their competitors’ products and services, allowing them to fine-tune their own price strategies and stay ahead of the game. It’s also used as a tool for manufacturers to ensure retailers are compliant with pricing guidelines for their products. Market research organizations and analysts depend on web data extraction to gauge consumer sentiment by keeping track of online product reviews, news articles, and feedback.

There’s a vast array of applications for data extraction in the financial world. Data scraping tools are used to extract insight from news stories, using this information to guide investment strategies. Similarly, researchers and analysts depend on data extraction to assess the financial health of companies. Insurance and financial services companies can mine a rich seam of alternative data scraped from the web to design new products and policies for their customers.



 

Who this course is for

  • Beginners to web scraping

 

Course content

  • Introduction
    • Introduction
    • What is Web Scraping and Web Crawling
    • What is Robot.txt
    • Legality of Web Scraping
    • Checks before web scraping
  • Python Setup
    • Installing Python on Windows
    • Installing Python on Macs
    • Create a virtual environment on Windows
    • Activate a virtual environment on Windows
    • Create a virtual environment on Macs
    • Activate a virtual environment on Macs
    • Update pip
    • Install Beautiful soup
    • Install Scrapy
    • Installing Visual Studio Code
  • Web Scraping with Python and Beautiful Soup
    • What we will scrape
    • Building the web scraping script : part 1
    • Building the web scraping script : part 2
    • Prototyping the script: Part 1
    • Prototyping the script: Part 2
    • Prototyping the script: Part 3
    • Prototyping the script: Part 4
    • Prototyping the script: Part 5
    • Testing the script
  • Web Scraping with Python and Scrapy
    • Create a Scrapy project
    • Components ofa scrapy project
    • Scrapy architecture
    • Creating a Spider: Part 1
    • Creating a Spider: Part 2
    • Scraping data with Scrapy shell: Part 1
    • Scraping data with Scrapy shell: Part 2
    • Testing the Scrapy Spider
  • Scraping Amazon Data with Python
    • Create and activate a virtual environment
    • Install Python Packages
    • Create a Python File
    • Create variables
    • send emails from Python
    • Create functions: Part 1
    • Create functions: Part 2
    • Create functions: Part 3
    • Testing the script
  • Web Scraping YouTube Data with API & JavaScript
    • What is an API
    • YouTube Data API
    • Using GoogleSheets
    • Building JavaScript Scraper : Part 1
    • Building JavaScript Scraper : Part 2
    • Building JavaScript Scraper : Part 3
    • Testing the first scraper
    • Building the second scraper
    • Testing the second scraper
  • Microsoft 365 and Power Automate Setup
    • Microsoft 365 Business Standard Setup
    • Getting started with Microsoft 365
    • What is Power Automate
  • Automating Web Scraping with No Code
    • Installing Power Automate Desktop
    • Explore Power Automate Desktop
    • Automate web scraping
    • Scrape Amazon website data
    • Scrape Ebay website data
    • Scrape Jobs website data
    • Scrape Hackernews website data

 

Web Scraping Projects for BeginnersWeb Scraping Projects for Beginners

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