BIOENG 245
Introduction to Machine Learning for Computational Biology
Genome-scale experimental data and modern machine learning methods have transformed our understanding of biology.This course investigates classical approaches and recent machine learning advances in genomics including: 1)Computational models for genome analysis. 2)Applications of machine learning to high throughput biological data. 3)Machine learning for genomic data in health. This course builds on existing skills to introduce methodologies for probabilistic modeling, statistical learning, and dimensionality reduction, while grounding these methods in understanding genomic information.
Topics
- This course aims to equip students with a foundational understanding of computational and machine learning techniques used in genomics and computational biology.
- Students completing this course should have a better understanding of some of the challenges in machine learning as applied to biology Students completing this course should have stronger programming skills. Students completing this course should have the ability to apply simple statistical and machine learning techniques to complex genomics data
Official catalogue course objectives and student learning outcomes
Sources
- Course catalogue ↗2026-2027