About the course...

Beautiful Data: The Art and Science of Visualization

In this course, students will learn how to make effective and beautiful data visualizations. We will study the theory and concepts of effective visualization drawing from computer science, statistics, psychology, and art and design. We will also cover the skills and techniques needed for the creation of both data exploration and data communication, including visual storytelling. Examples and case studies throughout the semester will be drawn from multiple disciplines, including physics, biology, health science, social science, geography, business, and economics. Students will practice their skills through visualization critiques and by analyzing and visualising data with standard plotting tools, including Google, Excel, and Tableau. Additionally, students will practice and master visualization skills and gain experience working with real data and real stakeholders through a Service-Learning partnership with a Boston-area non-profit organization. No prior experience with computer science or statistics is required.

Preq: None.

NUPath Attributes (PENDING): With Service Learning, Analyzing/Using Data, NU Core Experiential Learning, Integration Experience.

HONR 1310: Beautiful Data: The Art and Science of Visualization

Time and Location: Wednesdays and Fridays from 11:45am - 1:25pm, Ell Hall 411

Instructor: Prof. Michelle Borkin (m.borkin@northeastern.edu), Office 302E WVH.
    Office Hours: Wednesdays 2:30-3:30pm, WVH 302E (inside 302 suite, third floor).

Teaching Assistant: Ryan Perny (perny.r@husky.neu.edu).
    Office Hours: Tuesdays 2-3pm, WVH 302A (inside 302 suite, third floor).

Teaching Assistant: Sarah Wessel (wessel.s@husky.neu.edu).
    Office Hours: Thursdays 4:30-5:30pm, WVH 302E (inside 302 suite, third floor).

Service-Learning Teaching Assistant: Erykah Gomes (gomes.e@husky.neu.edu).
    Office Hours: Thursdays 3-4:30pm, Hastings 233 (2nd floor).

Discussion Forum: Piazza



**Schedule is subject to change as guest lectures are incorporated into the lecture line-up.