Case Studies in Biomedical Data Science

Description from DukeHub

This course will highlight how biomedical data science blends the field of biostatistics with the field of computer science through the introduction of 3 to 5 case studies. Students will be introduced to analytic programs typically encountered in biomedical data science and will implement the data science and statistical skills introduced in their previous coursework. Pre-req: Biostat 826 or equivalent content; Instructor Permission Required. Credits: 3

Skills

• data and statisticsdescription: "data science" and 4 more

AI-resilient: 0 of 5 0/5

• No: Physical, lab or field work
• No: Live work with people
• No: Judgment someone is accountable for
• No: A craft you practice with your hands or body
• No: Small, in-person format

The checks lean on Microsoft Research, Working with AI (2025), which found generative AI applies least to physical work and hands-on work with people. A signal, not a promise. How the score works

More in BIOSTAT

• Introduction to Statistical Theory and Methods II BIOSTAT 704
• Applied Biostatistical Methods II BIOSTAT 705
• Introduction to the Practice of Biostatistics II BIOSTAT 706
• Clinical Trial Design and Analysis BIOSTAT 708
• Introduction to Causal Inference BIOSTAT 709
• Analysis of Correlated and Longitudinal Data BIOSTAT 718

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