In our introductory course on Python for data engineering, you’ll get an overview of the Python programming language and how you can use it for data engineering.
You will learn to code using real-world mobile app data while learning key Python concepts such as lists and for loops. You’ll also learn how to update variables, how to work with different kinds of data, how to manipulate Python dictionaries, and how to use custom functions to speed up your workflow.
Additionally, we’ll cover some coding best practices that’ll help you build good habits right from the start, and show you how to use Jupyter Notebook, a popular tool used in the Data Engineering workflows for easy sharing of data engineering projects.
At the end of the course, you will combine all the skills you have learned to create your own data science portfolio project. In this guided project, you’ll analyze different app profiles on the iOS App Store in order to make recommendations for the most profitable types of apps to develop.
By the end of this course, you'll be able to:
Learn to use Python for Data Engineering
Programming in Python
Learn the basics of programming in Python.
Variables and Data Types
Learn about variables and data types.
Lists and For Loops
Learn to analyze data using lists and for loops.
Learn to answer more granular questions using conditional statements.
Learn to build frequency tables using dictionaries.
Learn how to speed up your workflow using functions.
Learn more about using functions to write better code while avoid common pitfalls.
Project: Learn And Install Jupyter Notebook
Learn the basics of using Jupyter Notebook.
Profitable App Profiles for the App Store and Google Play Market
Learn to combine the skills you learned in this course to perform data analysis.