Course Prerequisites

(i) Graduate Standing; (ii) familiarity with college statistics and computer programming concepts will be helpful but not mandatory.

Course Description

The world is awash with increasing amounts of data, and we must keep afloat with constant perceptual and cognitive abilities. Visualization provides one means of combating information overload, as a well-designed visual encoding can supplant cognitive calculations with simpler perceptual inferences and improve comprehension, memory, and decision making. Furthermore, visual representations may help engage more diverse audiences in the process of analytic thinking. In this course, we will study techniques for creating effective visualizations based on principles from graphic design, visual art, perceptual psychology and cognitive science. The course is targeted both towards students interested in using visualization in their own work, as well as students interested in building better visualization tools and systems. In addition to participating in class discussions, students will have to complete multiple data analysis/data visualization assignments as well as projects. Students will be expected to design, build, and present their findings. (Please note that this is not a programming language course. Students will only be expected to learn how to apply the visualization design principles taught in class using at least one off-the-shelf visualization package. Students with a coding background will be given the chance to work on visualization projects that involve coding only if they choose so.)

Course Objectives

●   This course is designed to provide students with the foundations

necessary for understanding and extending the current state of the art in data visualization. • Explain and motivate the usage of data visualization as a business intelligence tool • An understanding of the key techniques and theory used in visualization, including data models, graphical perception and techniques for visual encoding and interaction • Have an analytical thinking mind set. Understand data driven problem solving and be able to wrangle, manipulate, and visualize data to drive insight • Introduce a systematic background for students to create their own visualization design projects • Expose to available popular visualization software and provide hands-on experience • Provide insightful case studies of using Data Visualization in industrial settings • Apply analytics and data visualization in a strategic context

Course Structure

Online: This course is conducted fully online, meaning you do not have to be on campus to complete any part of it. You will engage with the course content and participate in activities through NYU Brightspace accessible at https://brightspace.nyu.edu. There will be a synchronous session where you will join live via Zoom for real-time interaction with your instructor and peers.

* If your course follows a different modality, e.g. Hybrid, Blended, etc, please make the necessary adjustments.

Grade Breakdown (%) [Note: adjust this to fit the structure of your course]

●   10% - Class preparation and participation

●   40% - Assignments/case studies (create specific visualizations using course provided data)

●   25% - Midterm Project (individual) (design/create your individual visualizations and presentation)

●   25% - Final Project (design/create individual/group visualizations, using data from specified public sources)