Developed a sophisticated multi-class sentiment analysis system using BERT, achieving 80.69% accuracy on aspect-based opinion classification. The project successfully addressed class imbalance challenges through weighted loss functions and optimised model architecture, demonstrating robust performance in categorising opinions as positive, negative, or neutral.