Diving into the world of data analytics and R programming, especially when exploring the rich datasets of the All of Us Research Program, can be both exciting and daunting. To facilitate this learning journey, HSLS has designed the “Applying Probability and Data with R to All of Us Datasets” self-paced learning module* to act as a perfect complement to the “Introduction to Probability and Data with R” course on Coursera, created by Duke University’s Professor Mine Çetinkaya-Rundel. This module is not just about bridging the gap between foundational R programming and statistical concepts; it’s tailored to specifically illuminate the All of Us coding templates, ensuring that the concepts covered are directly applicable to the real-world data challenges of the database. With the flexibility to engage with just the Duke course, solely our HSLS module, or a combination of both, you can tailor a learning experience that perfectly suits your educational needs and aspirations.
If you choose to take the Coursera course—either independently or alongside our HSLS module—you’ll have the opportunity to earn a certificate of completion at the end of the eight-week term, provided you meet the course deadlines. This certificate, available at no cost to those affiliated with the University of Pittsburgh, serves as formal recognition of your dedication and achievements. To further enhance your learning, HSLS offers additional support for users through R office hours and specialized workshops. This comprehensive support network is designed to help you navigate any obstacles that arise, with a dedicated HSLS instructor available during office hours to address course-related inquiries or specific coding challenges. The ultimate goal of this module is to equip you with essential R skills, enabling you to confidently manage All of Us datasets for research in underrepresented communities and apply your newfound knowledge to a variety of projects.
~Alexis Cenname
*HSLS self-paced modules require a Pitt username and password (to log in via Pitt Passport). UPMC residents and fellows who do not have a Pitt username can request access to a self-paced module. HSLS live classes are open to University of Pittsburgh faculty, staff, and students, as well as UPMC residents and fellows.