The rapid advancements in Artificial Intelligence (AI) have opened up new frontiers for personalized education and professional development. This paper presents a novel framework for an AI-driven personalized coaching system that leverages dynamic behavioural modelling to cater to the unique needs of students and professionals. The proposed system utilizes a multi-modal approach, integrating data from user interactions, physiological sensors, and performance metrics to build a comprehensive and dynamic model of the user's cognitive and affective states. This model, in turn, informs a personalized coaching engine that provides real-time, context-aware guidance and support. We introduce a unique architecture that combines deep learning for behavioural prediction with a rule-based expert system for coaching interventions. The paper details the design and implementation of the system, including the data collection and processing pipeline, the dynamic behavioural modelling algorithm, and the personalized coaching strategies. We present a case study with sample data to demonstrate the system's effectiveness in improving learning outcomes and professional skills. The results are benchmarked against traditional coaching methods, highlighting the significant advantages of our AI-driven approach. Finally, we discuss the potential for future improvements, including the integration of large language models for more natural and empathetic coaching interactions, and the exploration of novel physiological sensors for more accurate behavioural modelling. The proposed framework has the potential to revolutionize the fields of education and professional development, making personalized coaching accessible and affordable to a wider audience. The novelty of this work lies in the synthesis of dynamic behavioural modelling with a multi-modal data-driven coaching engine, which we believe is a significant contribution to the field and holds strong patent potential