LLMs in Practice: Real World Applications, Challenges and Success Stories offers a deeply applied, interdisciplinary perspective on how Large Language Models (LLMs) are being integrated into the real world―spanning industries, healthcare, education, governance, mental health, creative domains, and intelligent systems. The book presents a blend of technical insights, sector-specific applications, governance frameworks, and ethical considerations. Designed for both academic and professional audiences, it equips readers to responsibly deploy LLMs while fostering innovation, equity, and scalability. LLMs in Practice: Real World Applications, Challenges & Success Stories addresses a significant gap in current literature by offering a focused and practice-oriented examination of how Large Language Models (LLMs) are being applied across diverse real-world domains. While there is widespread academic and public interest in generative AI, there exists no single resource that cohesively captures its deployment frameworks, sector-specific applications, ethical considerations, and pedagogical integration―especially from a multidisciplinary and global perspective. This book provides deployment guidance, prompt optimization, and reliability strategies; governance frameworks, risk mitigation tools, and audit strategies; and offers case studies, instructional models, project templates, career-aligned examples, and skill-building paths.
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Kiran Jot Singh is currently an Associate Professor and Associate Dean (Academic Affairs) at Chandigarh University, Mohali, India. He has done PhD in the domain of Human Robot Interaction. He has also filed 12 patents with the Indian patent office. He is working on various funded projects, and his research interests include human robot/computer interaction, bio feedback and happiness studies through technology.
Dr. Shubham Mahajan is an academic and researcher, member of IEEE, ACM, and IAENG. He earned a B.Tech from Baba Ghulam Shah Badshah University, an M.Tech from Chandigarh University, and a PhD from Shri Mata Vaishno Devi University. He is currently Assistant Professor at Amity University, Haryana. His research spans artificial intelligence and image processing, including video compression, image segmentation, fuzzy entropy, nature-inspired optimization, data mining, machine learning, robotics, and optical communications. He holds patents internationally and has published widely in high-impact venues; he has edited several Scopus-indexed books. He has received multiple awards for research excellence and travel support from IEEE, among others. He has served as IEEE Campus Ambassador at premier institutes and promotes international collaborations. He participates in technical program committees and editorial boards for conferences and journals, shaping discourse in AI and image processing.
Divneet Singh Kapoor is currently an Associate Professor and Associate Dean (Academic Affairs) at Chandigarh University, Mohali, India. He has done PhD in the domain of signal processing and wireless communication. He has filed multiple patents with the Indian patent office and has been granted several, showcasing his innovative contributions to the field. His research interests span embedded systems, Internet of Things (IoT), robotics, and affective computing.
Dr. Khushal Thakur is Associate Dean – Academic Affairs and Associate Professor at Chandigarh University with over a decade of experience in Electronics & Communication Engineering. He holds a Ph.D. in Massive MIMO systems and has published extensively in reputed journals such as IEEE Access, Springer, and CRC Press. His research spans IoT, embedded systems, wireless networks, and AI, and he holds several Indian patents, including three granted ones. Dr. Thakur has contributed significantly to academic planning, curriculum design, and quality assurance, supporting initiatives aligned with NBA, NAAC, and ABET standards.
LLMs in Practice: Real World Applications, Challenges and Success Stories offers a deeply applied, interdisciplinary perspective on how Large Language Models (LLMs) are being integrated into the real world―spanning industries, healthcare, education, governance, mental health, creative domains, and intelligent systems. The book presents a blend of technical insights, sector-specific applications, governance frameworks, and ethical considerations. Designed for both academic and professional audiences, it equips readers to responsibly deploy LLMs while fostering innovation, equity, and scalability. LLMs in Practice: Real World Applications, Challenges & Success Stories addresses a significant gap in current literature by offering a focused and practice-oriented examination of how Large Language Models (LLMs) are being applied across diverse real-world domains. While there is widespread academic and public interest in generative AI, there exists no single resource that cohesively captures its deployment frameworks, sector-specific applications, ethical considerations, and pedagogical integration―especially from a multidisciplinary and global perspective. This book provides deployment guidance, prompt optimization, and reliability strategies; governance frameworks, risk mitigation tools, and audit strategies; and offers case studies, instructional models, project templates, career-aligned examples, and skill-building paths.
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