Intro to Python for Data Science

Work with a multi GB data set and build foundational data science skills.

Build foundational data science skills by working through a real-world case study using a real data set from Yelp.

This self-paced course is designed for people with some experience programming in Python, but who want to learn more about using libraries such as pandas for data science work.

After installing a fully featured distribution of Python, you'll learn key aspects of Jupyter notebooks and pandas before tackling a realistic business problem using a Yelp data set. Upon completion, you will have learned how to:

  • Approach a data set with a business problem in mind
  • Use common data science tools
  • Load data and transform it for analysis
  • Explore data through use of plots and statistics
  • Present findings in the most relevant way

In short, you will have built the foundation of skills required by any professional data scientist.

Curriculum Creator


Guy Maskall is a full-stack data scientist. He’s currently lead data scientist at CloudFactory, a mentor for Springboard's Introduction to Data Science and Intermediate Data Science: Python courses, and community manager for the introductory course.

Guy was previously head of data science at Cobalt Light Systems, a spin-out from the U.K.'s Rutherford Appleton Laboratory in Oxfordshire, where his machine learning work on the INSIGHT100 liquid explosive detection system fuelled company export growth of 300 percent, leading to the MacRobert Award and the Queen's Award for Enterprise, and the subsequent acquisition by Agilent Technologies in 2017.

Frequently Asked Questions

When does the course start and finish?
The course starts now and never ends! It is a completely self-paced online course - you decide when you start and when you finish.
How long do I have access to the course?
How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own.

Get started now!