ai-in-science
3 free lessons tagged ai-in-science across Science. Each one is a short sequence of focused steps with narration and a five-question quiz at the end — take them in any order, no signup required.
How Scientists Use AI: Tools Across the Research Cycle
AI touches nearly every stage of research, from reading the literature to analyzing data to writing the paper. Learn the categories of AI tools scientists use, the crucial difference between general assistants and specialized scientific AI like protein-structure predictors, and the caveats, hallucinated citations and reproducibility, that make rigor essential.
AI in Research: Integrity, Reproducibility, and Limits
Using AI in research responsibly means protecting the standards that make science trustworthy. Learn the integrity rules, disclosure, authorship, and the line between assistance and fabrication, why reproducibility and transparency constrain AI use, what AI genuinely cannot do in the scientific method, and how peer review and honest reporting keep AI-accelerated science reliable.
AI for Literature Review, Data Analysis, and Coding
A practical guide to the research workflows where AI helps most. Learn how to use AI to search and synthesize the literature (and verify it), write and debug analysis code even without being a programmer, run and interpret statistics, and draft scientific writing, all with the verification and reproducibility discipline that keeps the work rigorous.