This course offers a hands-on introduction to machine learning (ML) and artificial intelligence (AI) in bioinformatics. Designed for those with a working knowledge of Python (or similar languages), it focuses on the practical application of existing ML/AI tools to solve real-world biological data challenges.
You will explore how AI and ML are applied across a range of bioinformatics tasks and investigate the factors that influence their performance-such as data quality, integration, model explainability, ethical considerations, regulatory issues, and infrastructure. By the end of the course, you'll have the foundational skills to apply AI methods to biological data and evaluate their effectiveness in research and clinical contexts
Prerequisite Skills: Working knowledge of Python or similar programming language
Students may still enroll if they missed the 1st class session. However, they need to communicate with the instructor via Canvas and catch up on all missed work prior to the 2nd class meeting.
7/25/2025: Course format change. Please review full schedule for details.
This class is offered in an online synchronous format. Students are expected to log into this course via Canvas at the start time of scheduled meetings and participate via Zoom, for the duration of each scheduled class meeting.
To see all meeting dates, click "Full Schedule" below. No meeting on November 11, 2025.
You will be granted access in Canvas to your course site and course materials approximately 24 hours prior to the published start date of the course.
Required Tools and Materials: Google Colab account (Python 3 environment ready).
