COURSE

Python for Data Science: Fundamentals

In our introductory course on Python for data science, you’ll get an overview of the Python programming language and how you can use it for data science.

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 Science workflows for easy sharing of data science 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:

  • Understand the fundamentals of programming in Python.
  • Understand the fundamentals of data science.
  • Use Jupyter Notebook.
  • Build a portfolio project.

START LEARNING

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Learn to use Python for Data Science

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.

Conditional Statements

Learn to answer more granular questions using conditional statements.

Dictionaries and Frequency Tables

Learn to build frequency tables using dictionaries.

Functions: Fundamentals

Learn how to speed up your workflow using functions.

Functions: Intermediate

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.