Master essential system identification techniques and build robust data-driven models with this comprehensive guide. Explore foundational discrete-time linear system theory, core estimation theory, and practical signal processing. Learn to develop mathematical models from observed data, covering LTI systems, non-parametric/parametric models, and state-space approaches. An indispensable resource for engineering students, control systems professionals, and researchers seeking to enhance their understanding of system modeling and process operations. Features real-world case studies and embedded MATLAB codes for hands-on training.