The objective of this work is to illuminate the emerging research areas, technological advancements, and future directions in the fields of nonlinear dynamical systems and control. This proposal encompasses a range of disciplines, including mathematical modeling, stability analysis, bifurcation theory, and chaos theory, all of which are pertinent to the study of nonlinear dynamical systems. The text explores the dynamics of complex systems and their behavior in response to nonlinear interactions. Additionally, it delves into control theory and optimization techniques applied to nonlinear dynamical systems. The text encompasses subjects such as adaptive control, optimal control, robust control, and hybrid systems. Conversely, a compelling aspect of machine learning pertains to the data-driven identification of the governing dynamical equations. Conventionally, the advancement of nonlinear dynamics has been characterized by an approach that involves the invocation of fundamental principles and intuitions in the formulation of theoretical explanations for observed phenomena. In the contemporary era of big data, a fundamental challenge lies in the reconstruction of the underlying dynamic system through the analysis of existing data. This challenge reveals a significant gap in knowledge, particularly concerning artificial intelligence systems that accurately replicate physical systems. A further challenge pertains to the hybridization of contemporary controllers, predicated on control laws, with machine learning training algorithms. Each technique operates within its own discrete domain of control. To illustrate, aircraft control based on modern techniques is predominantly valid and safe. Nevertheless, under critical conditions, a novel data-driven controller can assume control of the aircraft based on millions of simulations of situations that are critical to classic controllers. In summary, the present work is intended for a broad audience, including researchers, academics, professionals, engineers, practitioners, students, and educators. The text addresses a range of subjects, including nonlinear dynamics, control systems, and machine learning. Consequently, it provides valuable insights, cutting-edge research, and practical applications to readers seeking to explore and advance their knowledge in these exciting fields