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Apr 15, 2026
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BIOTEC 555 - Machine Learning
Requirement Fulfillment: BIOTEC555 Machine Learning fulfills one of the 3 credit interdisciplinary courses in the Physics/Mathematics Biotechnology Category.
Delivery: Lecture
Machine learning is the study of how to build computer systems that learn from data in order to make pre-dictions, recognize patterns, and organize information. This course will explore both the underlying math-ematical theory and the practical application of methods for machine learning. Topics include supervised and unsupervised learning, dimensionality reduction, support vector machines, decisions trees, clustering, and neural networks. In addition, students will use advanced deep learning techniques to build models using large-scale data. Potential implementations include image recognition, signal processing, time series forecast-ing, recommender systems, reinforcement learning, computer vision, and sentiment analysis. Multiple case studies will be drawn from real-world applications including business, science, engineering, bioinformatics, healthcare, political science, epidemiology, and public health.
3 credits
Spring
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