Badminton is a popular sport that requires precision, accuracy and speed. The latest technological trends ensure that it has far reaching effects on sports including badminton. This paper provides an in-depth analysis of training assistant for badminton training to increase the training efficiency and effectiveness of the players. The concept of virtual reality is used to build the system architecture for badminton. Moreover, 3D-enabled MAX tools are used to construct and design the simulation for training fields by utilizing the data present in the system database. To estimate the system status, Kalman filter is used for observation and mathematical model's predictions. The Kalman filter also helps in calculating the arm movement and posture angle of badminton players. To address uncertainty and probabilistic reasoning, the Bayesian algorithm is used that relies on Bayes' theorem. The Bayesian algorithm develops a posture estimation method for badminton players to enhance their efficiency and accuracy. Experimental validation shows that the AI-based badminton training ensures that the system is more stable which enhances the efficiency of the prayers during competitions. The proposed approach outperforms the existing approaches, i.e., Serve, BackRub, Pouncing, and Counterattack. Moreover, the proposed approach outperforms or at least matched the existing algorithms in categorizing actions as Push Forward, Push Backward, Picking, Reverse Pick, and Lofty. [ABSTRACT FROM AUTHOR]