Python for Data Engineering Project
About this courseSkip About this course
Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!
Journey into the realm of becoming a Data Engineer and apply your basic Python knowledge of working with data. You will exercise various techniques in Python to extract data in multiple file formats from different sources, transform it into specific datatypes, and then prepare it for loading it into a database. You will perform these tasks with the help of multiple hands-on labs using Jupyter notebooks and IBM Watson Studio.
On completion of this course, you will have the confidence to employ Python for data engineering tasks such as extracting large data sets from multiple sources through the use of webscraping and APIs, transforming the data and making it ready for gaining valuable business insights.
NOTE: This course is not intended to teach you Python basics and has limited instructional content. Rather, it is intended for you to apply prior Python knowledge.
PRE-REQUISITE: The Python Basics for Data Science course from IBM is a pre-requisite for this project course. Before taking this course, please ensure that you have either completed the Python Basics for Data Science from IBM or have equivalent proficiency in working with Python and data.
At a glance
What you'll learnSkip What you'll learn
The objective of this course is to give you a solid understanding of what Data Engineering is.
In this course you will apply your Python skills for:
- Webscraping and data extraction using APIs Transforming data into specific data types ****
- Logging operations and preparing data for loading
- Working with Jupyter notebooks and IBM Watson Studio
Module 1: Python Project for Data Engineering
- ****Collect data using APIs and Webscraping
- Extract data from different file formats
- Transform data and prepare for loading
- Log data operations
- Share your Jupyter notebook in Watson Studio
- Submit work and review your peers