Course Description

In this digital world, data are readily available in all shapes and forms. Data science literacy – the ability to identify, evaluate, analyze, and present data in various formats – is an indispensable skill to be successful as young scholars. In this class, students will learn to critically evaluate how data are used to represent the world through maps, statistics, and graphs. Students will be guided on how to acquire credible data sources that are available in the public domain. Hands-on practice with web-based data visualization applications will allow students to explore topics of their interest and prepare a presentation that will deliver a data-driven story about their worldviews. Students will leave with essential data science knowledge and skills to confidently navigate today’s world as informed citizens and develop skills that transcend the capabilities of generative AI in the modern workplace. In this course, students will use Google Sheets as the primary tool.

Essential Questions

  • What are the common forms of data used to present the world?
  • What are key strategies for evaluating the credibility and validity of data presented on the internet?
  • How are data presented in visual formats? What are the common forms of data visualization?
  • For each type of data visualization: How do you interpret the data in graphic/map format?
  • How do you create different types of data charts in Google Sheets? How do you apply design touches to make the charts professional looking?
  • What are credible publicly available data sources for statistics about the world?
  • How do you present your own understanding of the world using data and visualization?

Other Information

  • Students will be required to bring a laptop or similar device. The Robinson Center can provide a device if your student does not have access.
  • This course requires some homework to be completed outside of the program day.

Who Should Apply

  • Students currently in 7th, 8th, 9th, or 10th grade

Week Overview

Date Theme/Topic 
Week 1 Introduction & Foundations: 

Data Science Literacy Misinformation vs Information, Basic Types of Data & Intro to Data Visualization 
Week 2 Data Organization, Descriptive Statics & Visualization:

Organization of Data, Descriptive Statistics, Population and Demographics, Working with Charts
Week 3                    Data Visualization & Interactivity: 

Energy & Environment, More Charts, Health Data, Scatter Plots
Week 4 Maps & Final Project

Drafting ideas, Working with Maps, Tableau Viz of the Day

Instructors

  • Will Patrone

Details

Cost

  • $1450
    • $1400 (tuition)
    • $50 (registration fee)

Time

9am - 2:30pm

Location

  • University of Washington Seattle Campus
  • Building and Room TBD

Date

  • June 30th- July 23rd, 2026
  • Monday - Thursday
    • First class is on a Tuesday

Refund and Transfer Deadlines

  • Full tuition refund: April 10th
  • 50% tuition refund: April 11th-May 8th
  • No refund: after May 8th