Week 1 — Welcome to PPUA 6302

Mahima Pushkarna
3 min readJan 9, 2017

PPUA 6302 will introduce you to various concepts in information design and visual analytics over 12 classes. Over the semester, you will attend five lecture classes with in-class exercises and five studio classes where you shall receive feedback on the three projects that you will be working on through the semester. We’ll also have two presentation days, for you to present the final outcomes of your projects to your peers, faculty and possibly, guests.

Start with some light reading for some perspective on design:
8 Unintuitive Lessons on Being a Designer by Julie Zhuo.

Course Objectives and Policies

PPUA 6302 will focus on the communication of insights found in data using visual principles introduced in the class. At the end of the class, you should be able to tell a compelling and convincing data story using visualizations.

Course Objectives

  • Gain a clear understanding of principles involved in information design and visualization
  • Understand and explore the variety of existing techniques and systems in information visualization
  • Gain an understanding of visual principles, perception and apply them first hand to create compelling visualizations
  • Develop a vocabulary around, and skills in critiquing different visualization techniques as applied to particular tasks, in order to evaluate visualization systems
  • Finally, learn how to tell a story visually using data.

Readings and Assignments

Readings for each lecture session will be provided one week before the session and should be completed prior to the assigned class. If you are unable to complete the readings on time, the topics will be covered in the corresponding class but you may not be able to take complete advantage of the class.

Please refer to Blackboard for logistics. Assignments are to be submitted via Blackboard and NuVu studio by the Sunday 5:00pm prior to the class. Peer feedback must be provided on NuVu studio by 5:00 pm Thursday to be eligible for credit and to ensure that your colleagues (and you) can incorporate the feedback in your work.

Projects & Papers

Deadlines will be provided for project stages, final project submissions and paper submissions. Late submissions will not be accepted.


You will be graded based on your participation in class discussions and team exercises, demonstration of concepts taught, quality of projects, papers, and presentations. Additionally, projects will be graded based on the progress and development of your projects at each touchpoint; in essence, you will be rewarded points on how much better you perform, compared to your previous submission. Therefore, push yourself.


This class will not be teaching any softwares, but you will need to use a visualization tool/language such as R, Rstudio in combination with a vector graphics editor such as Adobe Illustrator for your projects. Please refer to university resources to gain access to these tools. There are several online resources to learn these tools and languages and we encourage you to freely explore and acquire skills in these softwares and languages independently and outside of class time. There is an evolving resource page that will be made available to you on this publication.


Datasets will be provided to you for most assignments. In the case of an open assignment, you are free to pick a dataset of your liking but kindly ensure that the dataset does not violate any legal agreements that may bind it. If you do choose to use such a dataset, please provide appropriate documentation evidencing the permission to use the dataset, along with any limitations of use. In using these datasets, please anonymize any personal identifying information. Respect privacy, and always credit your sources.



Mahima Pushkarna

Design @Google, People + AI Research. Designing 'stuff' for human-AI understanding since 2017. Opinions mine.