BIOLOGY 724D-2
Foundations of Data Science for Biologists
Gregory A. Wray, Paul Magwene
Description from DukeHub
This course is the second of a two-semester sequence that provides an overview of computing and data analysis concepts and tools that are frequently used throughout the biological sciences. Topics covered include data filtering and restructuring; data visualization and effective communication; data science best practices for reproducibility, reusability, and discovery; and working effectively with big data. Students will learn how to leverage key tools from the Unix, R, and Python computing ecosystems.
Skills
- data and statisticsdescription: "data analysis" and 2 more
- programmingAI review: "Students will learn how to leverage key tools from the Unix, R, and Python computing..."
AI-resilient: 0 of 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
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