Data Science for Dynamical Systems | Practical Applications, Reinforcement Learning

Explore data science techniques for analyzing and controlling dynamic systems with this comprehensive course. Covers system identification, model predictive control, and more.

Introduction

This course provides an introduction to data science techniques for the analysis and control of dynamical systems. It covers topics such as system identification, model predictive control, and reinforcement learning, with a focus on practical applications.

Highlights

• Covers a wide range of data science techniques for dynamical systems
• Emphasizes practical applications and real-world case studies
• Taught by experienced researchers and practitioners in the field

Recommendation

This course is recommended for students and professionals interested in applying data science to the analysis and control of dynamic systems, such as in robotics, energy systems, and transportation. It provides a solid foundation in the theoretical and practical aspects of this rapidly growing field.