Learn from a beginner to an advanced level with 4 hands-on projects
What you'll learn
- web scraping
- data extraction
- data mining
- create your own dataset
- output data in Excel
- output your dataframe in PostgreSQL
- run SQL commands on your dataframe
In this Web Scraping APIs for Data Science 2021 | PostgreSQL+Excel course, students will get a comprehensive understanding of how to scrape data from an API available on a website (aff) (if available). Beginning with the basics and a beginner project, we will then move on to more advanced topics. Following that, there will be two different projects covered, followed by the advanced project. The data scraped of the wach project will be saved inside an Excel document. Our advanced level project will involve creating two datasets, each containing 5000 results. Basically, we want to merge the two dataframes (total: ten thousand results), save it in Excel, and then export the data into a PostgreSQL database so we can run SQL queries over the data.
Students must have a basic understanding of Python programming as a prerequisite to taking this course. Since we will not cover very difficult Python topics, we do not require professional programming knowledge. The most important characteristic is that you are interested in Web Scraping and Data Mining. If you are serious about gaining the knowledge that is taught in this Web Scraping APIs for Data Science 2021 | PostgreSQL+Excel course, you need to be willing to devote enough time to it.
The knowledge and experience you will gain from this Web Scraping APIs for Data Science 2021 | PostgreSQL+Excel course will allow you to create your own dataset and scrape your own data. These course resources will give you constant access to documents that you can refer to. Whenever you have a question or if a concept doesn't make sense to you, you can ask your question inside the Q&A – Forum. Your question will either be answered by the instructor or another student. Because of the community, you will never feel like you are learning by yourself.
Who this course is for:
- Data Enthusiasts who want to create their own datasets
Created by Alexander Schlee
Last updated 8/2021
Size: 2.1 GB