Augmented Reality (AR) is transforming the learning experience in anatomy and biology [1, 2]. by providing an engaging and interactive alternative to traditional teaching methods. Understanding complex anatomical structures has historically been challenging due to the limitations of textbooks, static models. AR overcomes these challenges by enabling students to explore high-fidelity 3D representations of the human body in real-time, fostering deeper spatial understanding and retention. The technology allows learners to interact with anatomical structures, receive immediate feedback, and learn at their own pace, beyond the constraints of the classroom. In addition to AR visualization, this project integrates an AI-assisted quiz and learning platform to further enhance anatomy education. By leveraging machine learning algorithms such as ensemble methods like Random Forests and Support Vector Machines (SVMs), coupled with SMOTE for class imbalance handling and cross-validation for robust generalization, the system offers adaptive quizzes, personalized learning recommendations, and real-time feedback. The platform dynamically adjusts to user interactions, ensuring a tailored and effective learning experience. Developed using Unity for AR functionalities, JSON for data management, and machine learning for prediction models, the system bridges the gap between theory and practice while promoting active and self-paced learning. This paper details the design, development, and evaluation of the AR-based Anatomy Learning Platform, highlighting its potential to revolutionize anatomy education by offering an accessible, immersive, and personalized approach. The platform is designed primarily for medical students, but it also supports general learners seeking to enhance their anatomical knowledge through immersive technologies.