Web Scraping with Beautiful Soup for Data Science

[mitsumi]

Last Update: 7/2021
Duration: 4h19m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 44.1 kHz, 2ch | Size: 1.97 GB
Genre: eLearning | Language: English

From Beginner to Advanced | 3 Hands-On Projects

What you'll learn:
Web Scraping
Beautiful Soup
Data Extraction
Web Scraping for Data Science
Data Mining
Data Scraping & Data Cleaning

Requirements:
Basic understanding of Python Programming

Description:
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.

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

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