The evolution of large language models (LLMs) and AI agents reveals a new era of interdisciplinary innovation, where the boundaries between fields like healthcare, law, education, and engineering are blurred. These advanced AI systems are being integrated into complex workflows that require reasoning, adaptability, and collaboration across knowledge areas. From assisting in medical diagnostics and legal research to enabling personalized learning and automating scientific research, LLMs and AI agents transform how problems are approached and solved. Their ability to process information, understand context, and generate responses positions them as powerful tools for handling challenges that require expertise. Advanced Interdisciplinary Applications of Large Language Models and AI Agents delves into the cutting-edge intersection of AI, machine learning, and data science. It explores the advanced applications of large language models (LLMs), AI agents, sentiment analysis, fuzzy logic, and computer vision. This book covers topics such as automation, business intelligence, and sentiment analysis, and is a useful resource for business owners, medical professionals, educators, computer engineers, academicians, researchers, and data scientists.