An excellent course in one of the hottest fields of the day. You will learn how to program in popular data science languages, how to clean and visualize data, how to make predictions using data, and how to work with collaboration tools.
Step 1 Python Introduction
Python Programming; Beginner
Learn the basics of Python, the programming language of choice for data analysis.
Python Programming; Intermediate
Learn some more aspects of Python, including modules, enumeration, indexing, and scopes.
Storytelling Through Data Visualization; Intermediate
Learn how to communicate insights and tell stories using data visualization.
Data Cleaning; Intermediate
Learn how to clean and combine datasets, then practice your skills.
Step 3: The Command Line
Command Line; Beginner
Learn the basics of the command line, a critical part of any data science workflow.
Git and Version Control: Intermediate
Learn the basics of git, a critical part of developing projects with teams.
Anyone interested in becoming a data scientist or using data science for their current job or side project. The course goes from beginner to advanced; no prior knowledge necessary other than basic math.
After barely graduating college, in 2011 Vik Paruchuri found himself working for the US Foreign Service. Bored, he taught himself how to code before venturing into the world of data science and machine learning.
After winning several Kaggle competitions, EdX hired Vik as a machine learning engineer. At EdX, Vik observed how technology could provide an alternative to the traditional education system.
Based on the many lessons he learned on his own journey, along with his observations about how successful data scientists learn, Vik started building Dataquest in 2015. It now has over 100,000 students worldwide.
All fields marked with red asterisks are required fields.