Purpose:
The volume of health information is growing exponentially. Health professionals need to manage this influx and use the information for the best health outcomes. To address this we designed a course to provide health professional students hands-on training to access, analyze and leverage big datasets for evidence-based practice, scholarship, and policy generation.

Methods:
We used an asynchronous online course across two universities and multiple degree programs to teach learners real-world skills for accessing, understanding, and analyzing large-scale datasets. The course ran for four weeks and consisted of seven modules. The course was structured to align with how adult professionals learn best: through relevance, autonomy, application, and reflection. Each module followed the same format that focused on building skills and integrating knowledge across healthcare disciplines. We recruited 30 students for the pilot of the course through email and in-person announcements.

Results:
We received an overwhelming number of applicants for the seats in the course. Of the selected learners, 83% (25/30) finished the course within 4 weeks. Learners rated their agreement with achieving the stated learning objectives at a mean of 4.0 (out of 5; based on a 1-5 agree/disagree scale) with 70% responding positively to all learning objective achievement statements (Somewhat Agree or Strongly Agree). Regarding the methods used to deliver the course content, 80% of the learners found the methods effective for teaching the material. From the work done in this course, several learners have decided to continue their projects to publication (3) or presentation (5).

Conclusions:
The online asynchronous course curriculum was an effective method to teach large-scale dataset analysis to a wide variety of health professions students. We plan to continue this course as a collaboration between the two universities.