Python Project for Data Engineering

Python Project for Data Engineering

This course is part of multiple programs.

Instructors: Ramesh Sannareddy

What you'll learn

Demonstrate your skills in Python for working with and manipulating data
Implement webscraping and use APIs to extract data with Python
Play the role of a Data Engineer working on a real project to extract, transform, and load data
Use Jupyter notebooks and IDEs to complete your project

Details to know

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Assessments

2 assignments

Taught in English

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There is 1 module in this course

Showcase your Python skills in this Data Engineering Project! This short course is designed to apply your basic Python skills through the implementation of various techniques for gathering and manipulating data.

You will take on the role of a Data Engineer by extracting data from multiple sources, and converting the data into specific formats and making it ready for loading into a database for analysis. You will also demonstrate your knowledge of web scraping and utilizing APIs to extract data. By the end of this hands-on project, you will have shown your proficiency with important skills to Extract Transform and Load (ETL) data using an IDE, and of course, Python Programming. Upon completion of this course, you will also have a great new addition to your portfolio! PRE-REQUISITE: **Python for Data Science, AI and Development** course from IBM is a pre-requisite for this project course. Please ensure that before taking this course you have either completed the Python for Data Science, AI and Development course from IBM or have equivalent proficiency in working with Python and data. NOTE: This course is not intended to teach you Python and does not have too much new instructional content. It is intended for you to mostly apply prior Python knowledge.

Module 1 introduces you to Extract, Transform, and Load operations basics. You will learn to extract required information from web pages using web scraping techniques and APIs. You will also access databases using Python and save the processed information as a table in a database.