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$29
  • Understanding of Web Scraping with Beautiful Soup & Python

In this course you will learn how to extract data from websites. The main tool will be the Beautiful Soup (BS 4) Library. Especially for people who work with data it is important to be able to create own datasets. Often we rely on datasets from someone else. This course should show all data enthusiasts how to scrape and store data in Excel Files.

After covering the basics, this course will focus on 3 different projects. We start with a Beginner Level Project. Afterwards we proceed with an intermediate project and finally we will cover an advanced topic. The requirement for this course is basic knowledge of Python Programming. Since we will not cover very difficult Python topics you do not have to be a professional. The most important characteristic is that you are curious about Web Scraping and Data Mining. You should be ready to invest time in gaining the knowledge which is taught in this course.

After this course you will have the knowledge and the experience to scrape your own data and create your own dataset. With the help of the course resources you will always have documents you can refer to. If you have a question or if a concept just does not make sense to you, you can ask your questions anytime inside the Q&A - Forum. Either the instructor or other students will answer your question. Thanks to the community you will never have the feeling to learn alone by yourself.

What you’ll learn

  • Web Scraping
  • Beautiful Soup
  • Data Extraction
  • Web Scraping for Data Science
  • Data Mining
  • Data Scraping & Data Cleaning

Are there any course requirements or prerequisites?

  • Basic understanding of Python Programming

Who this course is for:

  • Everybody who is interested in Web Scraping, for example Data Scientists
  • Professionals who want to create their own dataset without being dependent on some else

  • Basic understanding of Python Programming
  • Willingness to learn
  • Everybody who is interested in Web Scraping, for example Data Scientists
  • Professionals who want to create their own dataset without being dependent on some else
View More...
  • Section 1 : Introduction & Course Overview 1 Lectures 00:03:40

    • Lecture 1 :
  • Section 2 : Beautiful Soup - Basic Concepts 7 Lectures 00:33:33

    • Lecture 1 :
    • Imports, HTTP Requests, Soup Object
    • Lecture 2 :
    • Find & Find All
    • Lecture 3 :
    • Select & Select One
    • Lecture 4 :
    • Extract Attribute Values
    • Lecture 5 :
    • Navigate to Siblings &Parents
    • Lecture 6 :
    • Extract Links & URLs
    • Lecture 7 :
    • Find Elements - Alternative Syntax
  • Section 3 : Project No.1 - Level: Beginner 3 Lectures 00:19:05

    • Lecture 1 :
    • Overview & SetUp
    • Lecture 2 :
    • Extract necessary Data
    • Lecture 3 :
    • Dataframe and Excel File
  • Section 4 : Project No.2 - Level: Intermediate 5 Lectures 00:24:03

    • Lecture 1 :
    • Project Overview & SetUp
    • Lecture 2 :
    • Scraping necessary Data - Part 1
    • Lecture 3 :
    • Scraping necessary Data - Part 2
    • Lecture 4 :
    • Dataframe & Data Storage
    • Lecture 5 :
    • Scraping Multiple Pages
  • Section 5 : Project No.3 - Level: Advanced 5 Lectures 00:00:01

    • Lecture 1 :
    • Project Introduction & SetUp
    • Lecture 2 :
    • Combine URLs
    • Lecture 3 :
    • Extract Data from First Link
    • Lecture 4 :
    • Loop through all links and store results
    • Lecture 5 :
    • Scrape Multiple Pages
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Alexander Schlee,

Hi Everyone, my name is Alex and I know that a lot of Programming-Topics can be very confusing and overwhelming. My Goal is to share my knowledge in a very simple way. I'm focussing on Python, Selenium and the whole Web Scraping Process. Especially for my own Data Science and Machine Learning Projects, I need to understand the concepts behind Web Scraping and I want to share it with my students.
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