Learn Web Scraping with Python from Scratch

Python Web Scraping Tutorial. Use BeautifulSoup & Requests to scrape & crawl Craigslist directory with Python
4.14 (2191 reviews)
Udemy
platform
English
language
Programming Languages
category
Learn Web Scraping with Python from Scratch
51 678
students
31 mins
content
Feb 2019
last update
FREE
regular price

What you will learn

Installing Python Web Scraping libraries, BeautifulSoup & Requests.

Extracting URLs from a webpage.

Scraping text data from a webpage.

Crawling multiple webpages and scraping data from each of them.

Handling navigation links and move to next pages.

Saving scraped data into a CSV file with Pandas.

Overview about other popular web scraping frameworks.

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Our Verdict

Learn Web Scraping with Python from Scratch offers a practical introduction to BeautifulSoup, Requests, and Pandas for web scraping tasks. The course content is concise and project-oriented; however, it could be more accessible for absolute beginners due to occasional assumptions about prior knowledge. Moreover, the pacing might demand extra time investment from learners. Despite minor limitations, this Udemy course effectively illustrates core concepts necessary for mastering web scraping with Python.

What We Liked

  • Covers installing Python web scraping libraries BeautifulSoup and Requests.
  • Clear instructions for extracting URLs and scraping text data from a webpage.
  • Demonstrates crawling multiple webpages and saving scraped data into a CSV file with Pandas.
  • Includes an overview of other popular web scraping frameworks.

Potential Drawbacks

  • Content could benefit from more frequent updates to reflect website changes.
  • Explanations might be too brief for beginners without prior knowledge in HTML and CSS.
  • Instructor's pacing can be fast, making it challenging to follow along without rewatching certain parts.
  • Insufficient emphasis on why specific commands are used and lack of in-depth explanations.
Related Topics
2088396
udemy ID
15/12/2018
course created date
22/11/2019
course indexed date
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