Steve Brunton Courses

Physics Informed Neural Networks (PINNs) - Introduction and Applications

3 ratings

Introduction to Physics Informed Neural Networks (PINNs): combining neural networks with physical laws to solve complex problems in fluid dynamics and beyond. Explores advantages, applications, and extensions of this innovative approach.

• YouTube
• 35 minutes
• Self-Paced
• Free Video

Singular Value Decomposition

2 ratings

Comprehensive exploration of Singular Value Decomposition, covering mathematical foundations, applications in data processing, and implementation in MATLAB and Python for various real-world scenarios.

• YouTube
• 7 hours
• Self-Paced
• Free Video

Taylor Series and Power Series Made Easy - Review of Calculus

2 ratings

Comprehensive review of Taylor and Power Series with visual aids and coding examples in Python and Matlab. Covers definitions, expansions for sine and cosine, and practical implementations.

• YouTube
• 29 minutes
• Self-Paced
• Free Video

Fluid Dynamics

1 rating

Explore machine learning applications in fluid dynamics, from turbulence modeling to control strategies, with a focus on data-driven approaches and advanced computational techniques.

• YouTube
• 6 hours
• Self-Paced
• Free Video

Data-Driven Science and Engineering

1 rating

Explora técnicas avanzadas de aprendizaje automático, sistemas dinámicos y control con ejemplos prácticos en Matlab y Python, basados en el libro "Data-Driven Science and Engineering" de Brunton y Kutz.

• YouTube
• 20 hours
• Self-Paced
• Free Video

Data-Driven Control with Machine Learning

1 rating

Explore machine learning techniques for data-driven control, covering system identification, model reduction, and advanced control strategies like MPC and reinforcement learning.

• YouTube
• 11 hours
• Self-Paced
• Free Video

Control Bootcamp - Kalman Filter Example in Matlab

1 rating

Explore Kalman Filter implementation on inverted pendulum using Matlab, covering theory and practical application in dynamical systems and control engineering.

• YouTube
• 22 minutes
• Self-Paced
• Free Video

Quality Control and Non-Destructive Inspection Using the Multinomial Distribution

1 rating

Explore quality control principles through multinomial distribution, learning to assess batch reliability using non-destructive inspection methods and statistical sampling techniques.

• YouTube
• 14 minutes
• Self-Paced
• Free Video

Conjugate Priors Example - Normal Distribution and the Exponential Family of Distributions

1 rating

Explore conjugate priors through Normal distributions and the Exponential Family, demonstrating how Normal likelihoods pair with Normal priors for Bayesian inference.

• YouTube
• 19 minutes
• Self-Paced
• Free Video

Linear Systems - Control Bootcamp

1 rating

Analyze ordinary differential equations using eigenvalues and eigenvectors, laying the foundation for linear control theory in this comprehensive mathematical exploration.

• YouTube
• 25 minutes
• Self-Paced
• Free Video

Physics Informed Machine Learning: High-Level Overview of AI and ML in Science and Engineering

1 rating

Explore how to integrate physics into machine learning, enhancing model accuracy and efficiency in engineering applications. Learn to leverage prior physical knowledge across all stages of the ML process.

• YouTube
• 47 minutes
• Self-Paced
• Free Video

Probability Bootcamp

Master probability fundamentals from counting to advanced distributions, including CLT, Bayes' theorem, and random variables for data science applications.

• YouTube
• 10 hours 37 minutes
• Self-Paced
• Free Video

Physics Informed Machine Learning - Embedding Physics in AI and Discovering New Physics with ML

Discover how to enhance machine learning by embedding physics principles, creating interpretable models that incorporate symmetries, conservation laws, and sparse dynamics.

• YouTube
• 9 hours 56 minutes
• Self-Paced
• Free Video

Engineering Math - Differential Equations and Dynamical Systems

Master differential equations and dynamical systems for real-world modeling in fluid dynamics, weather systems, biomechanics, and control theory with comprehensive mathematical foundations.

• YouTube
• 22 hours 3 minutes
• Self-Paced
• Free Video

Engineering Math - Crash Course in Complex Analysis

Master complex analysis fundamentals from arithmetic to residues, exploring Euler's formula, analytic functions, and Cauchy integrals for differential equations modeling.

• YouTube
• 6 hours 28 minutes
• Self-Paced
• Free Video