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CS-502: Deep learning in biomedicine

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MATH-234(a): Probability and statistics

Ce cours enseigne les notions élémentaires de la théorie de probabilité et de la statistique, tels que l'inférence, les tests et la régression.

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Fundamentals, methods, algorithms and applications of network machine learning and graph neural networks

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BIO-322: Introduction to machine learning for bioengineers

Students understand basic concepts and methods of machine learning. They can describe them in mathematical terms and can apply them to data using a high-level programming language (julia/python/R).

COM-490: Large-scale data science for real-world data

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Artificial Neural Networks are inspired by Biological Neural Networks. One big difference is that optimization in Deep Learning is done with the BackProp Algorithm, whereas in biological neural netwo

ENV-540: Image processing for Earth observation

This course covers optical remote sensing from satellites and airborne platforms. The different systems are presented. The students will acquire skills in image processing and machine/deep learning to

MATH-432: Probability theory

The course is based on Durrett's text book Probability: Theory and Examples.
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MICRO-462: Learning and adaptive control for robots

To cope with constant and unexpected changes in their environment, robots need to adapt their paths rapidly and appropriately without endangering humans. this course presents method to react within mi