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Course Schedule and Dates

Data Visualization Analytics Certificate Delivery Modality, Class Schedule and Course Descriptions

See below course schedule for course topics and objectives.

Courses are delivered in asynchronous virtual modality, including opportunities for additional scheduled virtual meetings with instructors. The class syllabus will provide a course timeline with assignments, readings and exams with their respective due dates. Any added virtual sessions will be offered on weekday evenings and recorded for those who cannot attend due to work commitments. Students may meet with instructors during Office Hours or at scheduled times. Courses must be taken in order to take advantage of the scaffolding nature of the content.

Academic Year 2024-2025 Course Schedule

2024-2025 Cohort Course Schedule
Term   Course

Last Day To Register and Pay Course Fees

Course Dates AND CENSUS   
Summer Session 2024   DVA 10: Introduction to Data Visualization June 10 2024 June 17 - August 2, 2024             CENSUS June 28  
Fall Session 1 2024   DVA 11: Data Analytics for Visualization July 29 2024 August 5 - September 20, 2024 CENSUS August 16  
Fall Session 2 2024   DVA 12: Infographics and Story Telling for Visualization September 16 2024 September 23 - November 8, 2024  CENSUS October 4  
Winter Session 2024-2025   DVA 13: Visualization for Decision Making November 5 2024

November 12, 2024 - January 10, 2025 (includes holiday breaks) 

CENSUS November 23

Spring Session 1 2025   DVA 14: Designing for Data Visualization January 8 2025 January 15 - March 5, 2025         CENSUS January 26  
Spring Session 2 2025   DVA 15: Data Visualization Portfolio March 3 2025 March 10 - May 2, 2025           CENSUS  March 21  

Course Topics and Objectives:

DVA-10 and DVA-11: Introduction and Analytics

  • Identify appropriate data visualization techniques given requirements imposed by the data.
  • Analyze, critique, and revise data visualizations.
  •  Apply appropriate design principles in the creation of presentations and visualizations.
  • Describe the data analytics process starting with developing an understanding of the purpose of a data mining project.
  • Distinguish and develop different data analytics techniques such as prediction, classification, clustering, association rules, and collaborative filtering.
  • Solve various data visualization and analytics problems (marketing, production, financial, etc.) using software packages including Tableau, Excel, R, and Python.

DVA-12 and DVA-14: Design and Storytelling

  • Identify how to create graphics tailored to a particular audience.
  • Introduce basic perception and cognition concepts, and apply those concepts to information visualization designs. 
  • Gain a firm understanding of infographic design principles as they apply to both static and interactive 
  • Introduce mapping & cartography
 through interactive GIS (Geographical Information System Mapping).  
  • Develop an understanding of the fundamentals of communication and alignment around concepts required for effective data presentation. 
  • Provide an overview and develop an introductory level of competency on the use of several available software tools that can be used for data visualization. 

DVA-13 and DVA-15: Applied Skills

  • Combine the data with the background information (storytelling) that puts the charts, figures, and symbols into context for easy comprehension by decision makers.
  • Present key data in a manner that points to sound courses of action.
  • Design dashboards for a variety of business applications to generate insights for stakeholders and decision makers .
  • Allow for project-based opportunities to identify, understand, analyze, prepare, and present effective visualizations on a variety of topics. 
  • Emulate a real work environment to solve real world business problems and communicate through storytelling to a non-technical audience.