Submitted by Meera Roy
on
From the Department of Environmental & Occupational Health Sciences:
ENV H 490 Data Science in Public Health
Learn Applied Data Science Skills
Open to all majors.
Looking to master data science methods used in public health?
ENVH 490/590 is a hands-on course designed to move you beyond spreadsheets and into R programming, data visualization, and reproducible research.
Whether you are an undergraduate building a foundation or a graduate student ready to analyze your own datasets, this course provides both background knowledge of the method and practical experiences to sharpen your skills.
This course provide you with an introduction to R programming, and covers the essentials of developing Data Science analysis "pipelines", including (1) importing data, (2) data management (quality checks, cleaning, and the concept of tidy data), (3) data engineering (data feature design and dimension reduction), (4) data modeling, (5) data communication (visualization using tables and figures), and (6) data/code sharing to improve the rigor and reproducibility of data analyses. Data privacy and other data ethical concerns will also be covered in the course.
The course labs will provide hands-on exercises involving common analyses in bioinformatics, epidemiology, environmental exposure assessment, natural language processing, and solving classification and regression problems. While the course’s case studies utilize real-world public health datasets, the skills are broadly applicable to other fields.