This course focuses on applying data science methods to biological data. With the rise of high-throughput techniques in biology, massive datasets are now common, including genomes, metagenomes, transcriptomes, and more. The course equips students with the theoretical and practical skills to extract insights from such data. Students learn to work with the command-line interface, write scripts in Python and bash, and use data analysis and visualization techniques. They also explore supervised and unsupervised machine learning methods and design computational pipelines to answer biological questions using large datasets. The course combines online modules, tutorials, group projects, guest lectures, and practical assignments.
