NVivo Training

The SSRL offers regularly-scheduled training in NVivo 12 Pro for Windows, led by SSRL Qualitative Research Manager and Specialist and NVivo Certified Expert, Rachel Tang.

The two-hour introductory NVivo 12 Pro for Windows training session utilizes a hands-on approach with a sample data set. The instructor introduces users to working with data in NVivo (importing, opening, and organizing various file types), guides learners through exploring and coding data in order to analyze for themes, and demonstrates novel program features. This workshop is most helpful for beginners or those who would like a refresher on how to manage and categorize data in order to enhance their thematic analysis skills and gain overall insight as to how NVivo for Windows is used in qualitative research.

Registration is open to all University of Saskatchewan faculty, students and staff, and employees of government, non-governmental organizations and community-based organizations. Registrations are processed on a first-come, first-served basis.



$50.00 plus GST. A cancellation fee of $20.00 plus GST is assessed if canceled at least one week prior to the session. Refunds will not be issued if canceled within one week of the session.

Upcoming Sessions

  • Friday, October 25, 2019, 9:30 AM - 11:30 AM
  • Friday, November 22, 2019, 9:30 AM - 11:30 AM
  • Friday, December 6, 2019, 9:30 AM - 11:30 AM

All sessions are held in the Murray Library, Room 161.

For more information, please contact the course instructor at rachel.tang@usask.ca or (306) 966-6319.

SSRL YouTube Channel

The SSRL YouTube Channel features new and archived videos from select SSRL workshops, lectures and events.

SNA Discussion Group

Organized by our Social Network Laboratory (SNL), the Social Network Analysis Discussion Group was established to bring together faculty, students and the general public who have experience or an interest in exploring and studying social networks. Through a monthly discussion series, we hope the discussion group will help to build and enhance community, collaboration, and knowledge and awareness of social network analysis, covering areas that range from basic research on social networks to advanced methods of network analysis.