FA550 Data Visualization Applications

Course Catalog Description


Effective visualization of complex data allows for useful insights, more effective communication, and making decisions. This course investigates methods for visualizing datasets from a variety of perspectives in order to best identify the best solution for a given task. Students will use a number of tools to refine their data and create visualizations, including: R and associated visualization libraries, Tableau 2020, Gephi, and web-based applications.

Campus Fall Spring Summer
On Campus X X
Web Campus X X


Professor Email Office
Brian Moriarty brian.moriarty@stevens.edu Babbio Center – 629

More Information

Course Outcome

  • Develop knowledge of tools for visualizing datasets
  • Develop a programmatic understanding of translating data into useful visual forms
  • Develop a critical vocabulary to engage and discuss information visualization
  • Develop an understanding of data visualization theory
  • Understanding of ethical considerations for data visualization

Course Resources


  • Storytelling with Data -- Cole Knaflic; ISBN: 978-1119002253
  • R Data Visualization Recipes -- Vitor Bianchi Lanzetta; ISBN: 9781788398312
  • GGPlot2 Essentials: Great Data Visualization in R
  • R: Recipes for Analysis, Visualization, and Machine Learning -- Viswa Viswanathan, Shanthi Viswanathan, Atmajitsinh Gohil, Chiu Yu- Wei; ISBN: 9781787289598
  • Mastering Gephi Network Visualization -- Ken Chevren; ISBN: 9781783987344
  • Learning Tableau 2020, 4th Edition -- Milligan, Josh; ISBN: 978-1800200364

Additional References

    There are many solid texts available through Safari Books Online including, but certainly not limited to:
  • Interactive Data Visualization for the Web, by Scott Murray; ISBN: 978-1-4493-3973-9
  • Data Visualization with d3.js, by Swizec Teller; ISBN: 978-1-78216-000-7
  • Data Visualization: A Successful Design Process, by Andy Kirk; ISBN: 978-1-84969-346-2
  • The Functional Art, by Albert Cairo; ISBN: 978-0-13-304118-7


  • Download the latest version of Tableau Desktop here:
  • Click on the link above and select Get Started. On the form, enter your school email address for Business E-mail and enter the name of your school for Organization.
  • Activate with your product key: xxxxx-xxx-xxx [Editor Note: the key will be provided once the class starts]
  • Already have a copy of Tableau Desktop installed? Update your license in the application: Help menu -> Manage Product Keys

Are your students new to Tableau? Share our free Data Analytics for University Students guide to help them get started. Students can continue using Tableau after the class is over by individually requesting their own one-year license through the Tableau for Students program here Need help? Find answers to frequently asked questions here.

TABLEAU COURSE MATERIALS: All Tableau course materials are available in the shared Files directory for this course.

Data Sets:


Grading Policies

Homework 50%
Discussion Board Submissions 10%
Individual Project Proposal 10%
Individual Project Final Submission 30%

Lecture Outline

Topic Reading Assignments
Week 01 Introduction to Data Visualization Required: Knaflic, Introduction and Ch. 1 Lanzetta: Installation and Introduction + Plotting Two Continous Variables In-Class: Review Syllabus Install R, Tableau, Gephi; Sign up for Datawrapper, Plotly
Week 02 Introduction to ggplot2 Required: Knaflic, Ch. 2 Lanzetta, In-Class: ggplot2 overview and exercises Understand the Context exercise
Due: ggplot2 assignment due via Canvas
Week 03 Introduction to summarizing with dplyr Required: Knaflic, Ch. 3 In-Class: additional ggplot2 content dplyr overview and usage Choosing an Effective Visual exercise Presentation of select homework submissions
Week 04 General visualization principles using R Required: Knaflic, Ch. 4 In-Class: Additional R visualization methods Identify and Eliminate Clutter exercise Due: Assembling an R visualization presentation assignment due via canvas
Week 05 Introduction to Creating Charts and Dashboards Using Tableau Required: Knaflic, Ch. 5 In-Class: Introduction to Tableau 2020.3 Focus attention exercise Presentation of select homework submissions
Week 06 Introduction to Mapping in Tableau Required: Knaflic, Ch. 6 In-Class: Introduction to Mapping in Tableau 2020.3 Think like a designer exercise Due: Tableau charts, dashboards, and mapping assignment due via Canvas
Week 07 (More) Advanced Topics in Tableau Required: Knaflic, Ch. 7 In-Class: Introduction to (more) Advanced topics in Tableau 2020.3 Tell a story exercise Presentation of select homework submissions
Week 08 Introduction to Gephi and Network Visualization Solutions Required: Knaflic, Ch. 8 In-Class: Introduction to Gephi Storytelling with data process exercise Due: Gephi /Network Visualization assignment submission due via Canvas
Week 09 Using R and Tableau as Complementary Tools Required: Knaflic, Ch. 9 In-Class: Working with R and Tableau together Developing a story exercise Presentation of select homework submissions
Week 10 Introduction to Datawrapper and Online Visualization Tools Required: Knaflic, Ch. 10 In-Class: Review of online data visualization tools Real-world scenarios exercise Due: Using online visualization tools assignment due via Canvas
Week 11 Visualization Applications 1 In-Class: Additional topics in data visualization TBD in-class exercise Presentation of select homework submissions
Due: Final project proposal due via Canvas
Week 12 Visualization Applications 2 In-Class: Additional topics in data visualization TBD in-class exercise Presentation of select project proposal submissions
Week 13 Project Review 1 Final project presentation 1 (Draft) In-Class: Presentations by cohort 1 of draft project
Week 14 Project Review 2 Final project presentation 2 (Draft) In-Class: Presentations by cohort 2 of draft project Due: Final project submission due via Canvas