With businesses generating and capturing increasing amounts of data, the ability to interpret and present insights in a persuasive way is more crucial now than ever before. Visualizing Data shows you how to make sense of your data, present clear evidence of your findings, and tell engaging stories all through data graphics.
In this four week course, students can progress at their own pace through the key steps of data visualization. The hands-on lessons will focus on techniques for data preparation — how to choose, create, and edit graphics, as well as best practices for presenting your visualizations.
In 2001, Stern became the first business school to establish its own center for exploring new models in teaching and learning. The NYU Stern Learning Science Lab is a team of creatives, educators, designers, and technologists who work closely with faculty to create engaging and interactive courses. Leveraging the resources of Stern and NYU at large, the team applies their expertise in user experience design, learning science, and video production to build immersive digital learning environments for business school education.
Online Learning Terminology
The term "asynchronous" refers to courses or course elements that can be completed at any time within the parameters of the course schedule. Asynchronous activities are things you do independently, like watch videos and complete assignments, and interactions with others over time via email, discussion forums, collaborative documents, and other channels. The term "synchronous" refers to learning with others in real time using videoconferencing and other technologies. Our online certificate courses are asynchronous with optional synchronous elements.
This course is a non-credit, pass/fail program. To pass this course, you will need a cumulative score of at least 55%. Upon successful completion of this course, participants will receive the NYU Stern Certificate in Visualizing Data.
During this course, participants will:
Data Formatting and Analysis for Data GraphicsUse visual data exploration methods that aid in data understanding, learn techniques for data preparation including data formatting and cleaning, and identify the target audience and line of inquiry.
Creation, Refinement, and Presentation of Data GraphicsIdentify appropriate data visualization techniques to build data graphics, refine the data graphics to improve clarity, and tell stories with data graphics that will resonate with the audience.
Data Visualization Case Studies and ExamplesSee how data graphics are used in practice through case studies showcasing a unique approach to using data graphics in different settings.
Who Should Attend
Although there are no formal education or background requirements, this course is designed for participants who meet the criteria below. While we strongly encourage global participation, please note that all courses are taught in English. Proficiency in written and spoken English is required.
Years of ExperienceParticipants with all levels of work experience are welcome to attend
Job FunctionsIdeal for any job function
PrerequisitesIntended for individuals with basic knowledge of Microsoft Excel
The following agenda is a sample and subject to change.
- In order to access the course, you will receive login credentials via email on the start date of the course. Activation instructions for your login credentials will be provided.
Data Visualization Made Simple: Insights into Becoming Visual by Kristen Sosulski (Routledge) (available digitally)
Live Online Meetups with Faculty
- Our live online meetups provide you with the opportunity to engage face-to-face with Professor Sosulski. Please note that all online meetups are recorded and available for your viewing at a later time. Missing a meetup will not impact your grade, however we recommend attending all sessions.
- Please expect to invest about 10 to 12 hours of your time per week to course lessons, exercises, and assignments.
Week 1 (July 19th): Essentials of Visualizing Data
- Introduction to Data Graphics and Design
- Design + Audience
- Live Online Meetup 1: July 22nd at 8:00 PM ET
Week 2 (July 26th): Visualizing Comparisons
- Categorical Data, Graphics and Design
- The Report
Week 3 (August 2nd): Visualizing Locations
- Geospatial Data, Graphics and Design
- The Dashboard
Week 4 (August 9th): Visualizing Time
- Temporal Data, Graphics and Design
- The Presentation
- Live Online Meetup 2: August 12th at 8:00 PM ET
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