Dynamical Modeling, Model Identification & Selection, Optimization, Feature Engineering, Control, Koopman Operator
Sub Category
- Data Science
{inAds}
Objectives
- Model and simulate complex dynamical systems using both analytical and numerical techniques.
- Identify and build predictive models from data, including linear and nonlinear systems.
- Apply optimization and machine learning methods to train models and solve control problems.
- Design data-driven control strategies for real-world applications using advanced algorithms.
- Understand the fundamentals of dynamical modeling, including ODEs, PDEs, and state-space representations.
- Master linear model identification techniques, such as least squares, recursive estimation, and Dynamic Mode Decomposition (DMD).
- Learn optimization methods for machine learning, including gradient descent, stochastic optimization, and constrained optimization.
- Explore nonlinear model identification approaches, including Neural ODEs and Hammerstein-Wiener models.
- Develop feature engineering skills for dimensionality reduction and improved model performance.
- Apply model selection techniques, including cross-validation, LASSO, and sparse modeling (SINDy).
- Implement optimal and predictive control strategies, including Model Predictive Control (MPC) and differential predictive control.
- Analyze complex systems using Koopman operator theory and Extended Dynamic Mode Decomposition (EDMD).
Pre Requisites
- Basic knowledge of linear algebra (matrices, eigenvalues, eigenvectors).
- Introductory concepts in probability and statistics (helpful for data-driven modeling).
- Familiarity with optimization basics (gradient descent, constraints) is a plus.
- Basic understanding of machine learning concepts.
- Basic Python programming (loops, functions, arrays)
- A computer capable of running Python and Jupyter notebooks.
- Exposure to control systems or dynamical systems theory.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
{inAds}
Coupon Code(s)