Machine Learning, Dynamical Systems and Control

Foundational Courses & Content

Note that each section leads to a series of topics and/or lectures.


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Ethics & Artificial Intelligence

Level | All Levels

Lecture series by Nathan Colaner, instructor in the Departments of Management and Philosophy at Seattle University, as well as an instructor for the AI Institute in Dynamic Systems.



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Beginning Scientific Computing

Level | Undergraduate

Lecture series by J. Nathan Kutz. This website makes available all lectures for AMATH 301, Beginning Scientific Computing. This course provides an introduction to programming and the MATLAB scripting language. It is intended for engineering and physical sciences majors, providing a broad introduction to the power of numerical methods, scientific computing and MATLAB programming.



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Introduction to Signal Processing

Level | Undergraduate

Lecture series by J. Nathan Kutz. This series on signal processing is intended as a first course on the subject with data and code worked in both MATLAB and Python. The lectures are from the textbook Oppenheim, Willsky and Nawab, Systems and Signals.



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Intro to Engineering Math - Several Topics

Level | See Description

Lecture series by Steven L. Brunton

This lecture series presents a comprehensive introduction and overview to Differential Equations & Dynamical Systems. Dynamical systems are differential equations that describe any system that changes in time. Applications include fluid dynamics, elasticity and vibrations, weather and climate systems, epidemiology, biomechanics, space mission design, and control theory.

It is assumed that students have taken some calculus (but might not remember it) and are interested in modeling the real world.