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IT & SoftwareOther IT & SoftwareWeb Scraping

Modern Web Scraping Fundamentals with Python

Harness the power of Scrapy, BeautifulSoup and Selenium to boost your webscraping game!
Rating: 4.3 out of 54.3 (660 ratings)
33,379 students
Created by Jordan Sauchuk, Ligency I Team, Ligency Team
Last updated 2/2022
English
English [Auto]

What you'll learn

  • Understand the most important components for web scraping
  • Build their own web scraping projects
  • Learn core components of two of the most powerful scraping libraries: Scrapy and BeautifulSoup
  • Build multiple hands-on projects

Requirements

  • Internet Connection
  • Windows, Linux or Mac OS along with Anaconda and Spyder

Description

Getting access to the data you need can make or break you.

This is why Fortune 500 companies like Walmart, CNN, Target, and HSBC use web scraping to get ahead and stay ahead with data.

It’s the original growth tool and one of their best-kept secrets


…And it can easily be yours too.


From data spoofing to legalities, crawling libraries, maintenance, monitoring, more, building a safe and effective web scraper is risky business but it’s a skill every data scientist needs in their toolkit.


Today, we’re building one from scratch.


Hi, my name is Jordan Sauchuk. I’m an AI & Cybersecurity Engineer and a SuperDataScience instructor. I’m here to guide you step-by-step in building custom web scrapers in Python using Selenium, Scrapy and BeautifulSoup.


Welcome to Modern Web Scraping in Python.


At the end of this course, you will understand the most important components of web scraping and be able to build your own web scrapers to obtain new data, optimize internal processes and more.


Plus, familiarize yourself with some of the most common scraping techniques and sharpen your Python programming skills while you’re at it!


  1. First, learn the essentials of web scraping, explore the framework of a website and get your local environment ready to take on scraping challenges with Scrapy, BeautifulSoup, and Selenium.

  2. Next, set up a Scrapy crawler and cover the core details that can be applied to building datasets or mining.

  3. Next, cover the basics of BeautifulSoup, utilize the requests library and LXML parser, and scale up to deploy a new scraping algorithm to scrape top product information from Amazon

  4. Fourth, set up Selenium, and deploy it to solve a practical, real-world challenge. Plus, submit your solution to obtain useful feedback from me.

  5. Finally, test your newfound skills on a cybersecurity project that involves you finding highly-sensitive data.


We’l bel coding in Python, and using the automated testing suite Selenium, the Python framework Scrapy, and library BeautifulSoup to build web scrapers that can be customized to your specific needs.


But a thorough walk-through isn’t all you’re getting.


Access our student forum where you can interact with me and your fellow students. Ask me questions, receive input from other students and be inspired by the clever scraping solutions from your classmates.


Whether you’re a data scientist, machine learning or AI engineer who wants to access more data sources; a web developer looking to automate tasks, or a data buff with a general interested in data science and web scraping…


This course delivers an in-depth presentation of web scraping basics, methodologies and approaches that you can easily apply to your own personal projects, or out there in the real world of business.


Join me now and let’s start scraping the web together. Enroll today.


Who this course is for:

  • Anyone interested in harnessing the power of data, web scraping/crawling, and data mining.
  • Data Scientists who want to take their skills to the next level
  • ML/AI engineers that want to put together new sources of information or datasets
  • Web developers looking to obtain new information or automate tasks
  • Any one interested in programming or computer science
  • Software engineers or programmers looking to expand their skill set

Instructors

Jordan Sauchuk
Senior AI Advisor & Cybersecurity Engineer
Jordan Sauchuk
  • 4.4 Instructor Rating
  • 22,396 Reviews
  • 240,831 Students
  • 7 Courses

I'm a Senior AI Advisor, AI & Cybersecurity Engineer, and also the founder of the Threat Intelligence Group. My goal is to help provide my experiences and expertise that have been obtained through extensive research, many late nights, and cups of coffee.

I have been fortunate enough to work on a range of challenging projects worldwide and I have extensive experience specializing in technologies such as Python, R, JavaScript, C++, PHP, Tensorflow, Pytorch, Scikit-Learn, Keras, ReactJS, NodeJS, SQL, Plotly, Tesseract, Seaborn, and much more.

Recently, I have launched the Threat Intelligence Group as a means of providing cybersecurity awareness, integrating AI into the security domain, and also providing consulting services.

For more information please feel free to reach out to me on LinkedIn and Twitter. 

Ligency I Team
Helping Data Scientists Succeed
Ligency I Team
  • 4.6 Instructor Rating
  • 579,357 Reviews
  • 2,090,600 Students
  • 150 Courses

Hi there,

We are the Ligency team. You will be hearing from us when new Ligency courses are released, when we publish new podcasts, blogs, share cheatsheets and more!

We are here to help you stay on the cutting edge of Data Science and Technology. 

See you in class,

Sincerely,

Ligency Team!

Ligency Team
Helping Data Scientists Succeed
Ligency Team
  • 4.6 Instructor Rating
  • 561,553 Reviews
  • 2,090,598 Students
  • 105 Courses

Hi there,

We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more!

We are here to help you stay on the cutting edge of Data Science and Technology.

See you in class,

Sincerely,

The Real People at Ligency

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