Community Data Science Theory and Practice

This professional development course focuses on the collection, analysis, visualization and dissemination of information derived from structured public datasets.

You'll acquire a basic toolkit for navigating public datasets containing socio-economic, demographic, land-use and real estate data. You will not only develop a familiarity with core datasets like the Census, municipal business licenses and property datasets, but also a basic ability to understand and use most structured public datasets. While you won't necessarily fully master these datasets in this single course, you'll learn a set of skills and conceptual understandings to analyze and share information.

The focus will be on Canadian datasets typically used by professionals in fields such as urban planning, real estate, development, transportation, public policy, government, the non-profit sector and other related disciplines, whether in urban, suburban or rural communities.

The course provides a balance of "how," "what" and "why" of working with data and understanding its possibilities and limitations in the development of evidence-based decisions.


As exercises use Microsoft Excel, some mathematical competence and experience using basic Excel functions are required. We recommend Excel 2010 Fundamentals videos 1 through 5 on the Excel Functions YouTube channel

This course is available at the following time(s) and location(s):

After you have registered, click on "CONTINUE TO NEXT STEP" where you will be asked a few additional questions.

This course is available at the following time(s) and location(s):

Campus Session(s) Instructor(s) Cost Seats available  
Vancouver 4 Craig E Jones
Andy Yan
$761.25 0 Join Waitlist

What will you learn?

By the end of this course, you will be able to do the following:

  • Describe the fundamental elements of data
  • Explain the structure and importance of the Canadian Census
  • Acquire Canadian Census data and open data for B.C. at provincial and municipal scales
  • Assess a basic dataset
  • Form a research question that requires the use of public structured datasets and pragmatic approaches to research design
  • Describe best practices in data management
  • Perform the most commonly used operations in data analysis
  • Understand the inherently philosophical and political nature of data and its limitations
  • Understand the basics of communication and mobilization of knowledge generated through data analysis

How will you learn?

  • Lectures
  • Class discussions and applied exercises
  • In-class assignments

How will you be evaluated?

You will receive a post-course assignment, guidance and feedback.

Textbooks and learning materials

We will provide custom course materials.

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