This capstone course will build upon the praxis, analytics and skills developed in the Community Data Science Certificate. The focus is on actual design and implementation of a data analysis project that is both relevant and applicable to real-world problems. The format of the Studio will be highly interactive, favouring collaboration, coaching and mentoring. You will come to the course with a written proposal for a problem or research question to be workshopped with colleagues and instructors. Finally, you will confirm the validity of their methods and results through member-checking, methodology reports, and an in-class presentation of findings; incorporating appropriate critical feedback into your final product.
This course is available at the following time(s) and location(s):
What will you learn?
By the end of this course, you will be able to do the following:
- Collaborate with others on a data analysis project
- Define a research problem or question
- Design a research project
- Select appropriate data sources and methods
- Conduct analysis using suitable software packages and tools
- Document a data analysis project for transparency and reliability
- Present a narrative of your analysis results through summaries and visualizations
- Identify when critical feedback requires an amendment to a project
- Disseminate findings online according to three modes: summary and highlights,
methodology, and raw data plus documentation
How will you learn?
- Class discussions and applied exercises
- Team-based data analysis project
- Team-based final capstone presentation
How will you be evaluated?
You will receive a post-course assignment, guidance and feedback.
Hardware and software requirements
- Students are required to bring a PC laptop (with full administrative privileges) to each class.
- A recent install of Microsoft Excel.
- Beyond 20/20 (an open-source data publishing, dissemination and analytics tool), installed during the CDSC101 course.
- Esri ArcGIS (graphical information systems software), installed during the CDSC102 course.
- R virtual online console (open-source statistical and data science tool), installed during the CDSC103 course.
- Tableau (data visualization tool), installed during the CDSC103 course.
- Online sessions in this course will be delivered through SFU's online course management system, Canvas. You will receive course details and Canvas access instructions on the first day of the course. You can check if your browser is compatible with Canvas here.
- New to online learning? See Online Programs and Courses for helpful videos and additional information.
Textbooks and learning materials
We will provide custom course materials.