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23 courses. Python and R are free in full; every other course opens its first two chapters as a preview and unlocks entirely with a subscription.
Learn to code the way biologists actually work — every example built on sequences, expression matrices and real experimental data.
From first script to publication-ready analysis pipelines
A biology-first Python curriculum. Every concept is introduced because a biological problem needs it — dictionaries are codon tables, loops scan genomes, dataframes hold expression matrices. Covers fundamentals, pandas/NumPy, Biopython, statistics and machine learning, and interactive Streamlit and Quarto reporting.
A field guide to data — tidyverse, Bioconductor and beyond
R taught as laboratory practice rather than computer science. Starts with the six data containers and base syntax, then works through the tidyverse, Bioconductor packages (Biostrings, DESeq2, edgeR, Seurat, biomaRt), statistical modelling, survival analysis and R Markdown / Shiny reporting.