Martin T. Wells, Ph.D., joined the Cornell faculty in 1987 and is the Charles A. Alexander Professor of Statistical Sciences. He is also a Professor of Social Statistics, Professor of Clinical Epidemiology and Health Services Research at Weill Medical School, an Elected Member of the Cornell Law School Faculty, as well as the Director of Research in the School of Industrial and Labor Relations. He teaches statistical methodology to undergraduate and graduate students in fields such as agriculture, biology, epidemiology, finance, law, medicine, nutrition, social science, and veterinary medicine as well as graduate courses in statistics.
Analysis Methods in Precision NutritionCornell Course
Course Overview
In this course, you will put your skills into practice with the groundbreaking “All of Us” (AoU) Research Program, one of the largest and most diverse health databases in the United States. You'll first explore the program's mission and scope, discovering the wide range of research questions possible with this remarkable dataset.
Before the course begins, you will complete training to access the AoU Researcher Workbench, where you'll apply your R programming skills to real-world health data. Building on this access, you'll analyze the database through hands-on exercises, uncovering insights that can advance precision medicine and improve health outcomes across diverse populations.
You are required to have completed the following courses or have equivalent experience before taking this course:
- Foundations of Precision Nutrition
- Evaluating Methods in Precision Nutrition
- Precision Nutrition in Research, Policy, and Practice
- R Primer in Data Analysis
Key Course Takeaways
- Explore the strategic goals of the AoU Research Program and the types of questions that can be investigated
- Create and analyze cohorts, concept sets, and datasets using R and the AoU Researcher Workbench
- Discuss the pipeline used for analyzing AoU data

How It Works
Course Author
Who Should Enroll
- Health and nutrition professionals
- Data scientists
- Biopharma professionals
- Healthtech entrepreneurs and consultants
- Medical scientists
- Food scientists
- Agriculture and food systems experts
- Graduate students, postdocs, and academic researchers
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