PHDA testimonials

If you would like to specify which course(s) you would like to see testimonials for, you may do so by selecting the course(s) from the list below and hitting the APPLY filter button. You may select more than one course. Otherwise, the testimonials are listed below, in random order.
PHDA 04 Spatial Epidemiology and Outbreak Detection
"The labs and the access to the SRTL were the biggest strengths of these courses. The SRTL had all the software, and all the data, and was really easy to access, and was well maintained and organized. The labs were applied, and had very tangible learning outcomes associated with them. They were practical in purpose, and effective in implementation via the SRLT. The labs were very smooth and impactful."

Allyson Rayner, Curriculum Consultant

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PHDA 01 Working with Administrative Data
"The course was well structured. Through the course, I learned: a formal approach to developing, structuring and answering a research question using administrative data; how to clearly define the study population; how to develop a flow chart to illustrate, and guide, the development of an analytical dataset; and SAS skills. It was an excellent course and a good refresher for me, as it has been 5 years since I’ve done data analysis. A number of course assignments required me to pair with a fellow student and undergo peer review of one another’s code. It was interesting to see how my peer structured their code to produce their dataset. I enjoyed and learned a lot from this exchange. The flexibility of distance learning meant that it was possible to complete work at my own pace and schedule. It was also helpful to learn from students in different locations, who worked in related fields but had different strengths, skills and perspectives.

Finally, this course gave me experience working with administrative datasets and tools that can be difficult to access on the job. The opportunity to work with samples of real data exposed me to some of the challenges I could face at work in learning, cleaning, formatting and analyzing the data. I would highly recommend this course and the PHDA program to my colleagues. It’s a well-structured and organized program and provides a good theoretical and practical approach to population health data analysis."

Esther Parker, Senior Policy Analyst, BC Ministry of Health

 

PHDA 03 Population Health and Geographical Information Systems
"The GIS courses, PHDA 03 Population Health and GIS and PHDA 04 Spatial Epidemiology and Outbreak Detection provided the greatest benefits. They were excellent and introduced brand new skills for me. Prior to taking these courses I had some brief exposure to GIS within my Master’s program and through the free online PopData courses. The PHDA 03 and PHDA 04 course labs were very detailed and instructional, offering good balance between theory and practice. The courses generally had enough materials I could take away to continue working independently."

Sophy Zhang, Program Administrative Coordinator, Canadian Mental Health Association, BC Division

 

PHDA 06 Health Services Program Monitoring and Evaluation
"The Health Evaluation and Program Monitoring (PHDA 06) course really helped me land a job after graduation. PHDA 06 was different from the other PHDA courses. It felt a bit like a satellite course in the program as it included a health evaluation project rather than data analysis lab work. I learned a lot from the peer review process we used. I have applied evaluation skills that I learned from this course, including logic models, evaluation methodology, gantt charts and interview guides."

Jackson Flagg, Evaluation Lead

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PHDA 04 Spatial Epidemiology and Outbreak Detection
"Courses which benefited me the most are PHDA 03 Population Health and Geographic Information System (GIS) and PHDA 04 Spatial Epidemiology and Outbreak Detection.

I am really satisfied with these courses especially the hands-on experience gained while using ArcMap to map diseases and assess spatial dependences. Skills developed include generating choropleth map, joining attribute tables to shapefile and perform geographically weighted regressions."

Samuel Essien, PhD Candidate, School of Public Health, University of Saskatchewan