Machine learning (ML) is a subfield of artificial intelligence (AI) in which machines learn complex patterns from existing data and perform a task without being explicitly programmed to do so. Today, ML is everywhere. Google’s search algorithms, Netflix’s recommendation services, and many cars’ autopilot systems are prime examples of ML in action. ML is highly used in biology, too, where it can predict the occurrence of disease and advance precision medicine. But ML can still seem like a daunting and scary field to enter, especially for the inexperienced. In this 8-week course, we will translate ML concepts and algorithms into plain English, learning the basics of how ML works and how it is able to make such reliable predictions. Using the Python programming language, students will have a chance to implement an ML algorithm on a real biological dataset to differentiate cancers based on their gene expression profile. This course will focus on using ML in a biological context.

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After this course, students who are interested in this area can pursue Mentored Advanced Research (MAP) on topics such as:

1. Predicting the tissue of origin in cancer based on gene expression levels
2. Predicting which individuals have COVID-19 based on chest X-ray images
3. Predicting disease-associated regions of DNA using epigenetic information (Epigenetic information refers to chemical signatures on the DNA that do not alter the DNA sequence but affect how genes are expressed.)