You'll gain hands-on experience with critical data engineering tasks in Data Engineering Project with Python. In this project you will implement an Extract, Transform, Load (ETL) data pipeline by creating a Python script.

You will learn to work with an IDE similar to VS Code to create your Python program and execute your code in a Linux terminal window.

As a part of the project you will collect data from APIs and web scraping, extract data from diverse file formats, transform it for further analysis, and load it into a relational database. You'll also log data operations to ensure transparency and reproducibility.

Enhance your collaborative skills by sharing your project and participating in peer reviews to gain and provide constructive feedback. This module will equip you with the practical knowledge and skills to handle real-world data engineering challenges efficiently.

What you will learn:

After completing this course, you will be able to:

Use Python and an IDE to perform ETL tasks.
Utilize APIs and web scraping to perform data extraction
Transform data for analysis
Log operations and prepare data for loading

Course Syllabus

Module 1 - Extract, Transform, Load (ETL)

Getting Started with IDE
Extract, Transform, Load (ETL)
Web scraping
REST APIs and HTTP Requests
Web scraping and Extracting Data using APIs
Querying SQLite3 database

Module 2 – Final Project

Practice Project: Extract, Transform, and Load GDP Data
Final Project: Acquiring and Processing Information on World's Largest Banks

General Information

This course is self-paced.
This platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.

Recommended Skills Prior to Taking this Course

Working knowledge of the Python programming language (It is highly recommended that you complete the Python Fundamentals course from IBM prior to starting this project).

Data Engineering Project with Python

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