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ComputingLifeSci

A complete computational biology curriculum — 23 courses covering programming, databases, machine learning, genomics and research infrastructure. Written for biologists, not computer scientists.

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Programming for Biology

Python for Biologists
R for Biologists
Perl for Biologists
MATLAB for Biologists
SAS for Biologists
BioJava for Biologists

Data & Databases

SQL for Biological Databases
Bioinformatics Databases
Big Data Mining for Biologists

AI & Machine Learning

Machine Learning for Biologists
Artificial Intelligence for Biologists
MLOps for Biologists
AI Tools for the Bioinformatics Lab

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Artificial Intelligence for Biologists45 chapters

Chapter 3.1 — Just Enough Computer Science & Programming Concepts
Chapter 3.2 — Just Enough Mathematics: Statistics, Probability, Linear Algebra, Calculus

/Artificial Intelligence for Biologists/PART 3 — FOUNDATIONS REQUIRED FOR AI

Chapter 9 of 454 min read

Chapter 3.1 — Just Enough Computer Science & Programming Concepts

Learning Objectives Understand core programming concepts without needing to code fluently Recognize why Python and R are the two dominant languages in bioinformatics + AI Introduction You do not need to become a…

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PreviousChapter 2.2 — Learning, Decision-Making, and Feedback Loops NextChapter 3.2 — Just Enough Mathematics: Statistics, Probability, Linear Algebra, Calculus