Mastering Prompt Engineering

Erscheinungsjahr 2025
ISBN: 978-0-443-33904-2
Verlag: Elsevier Inc

Buch, Englisch, 366 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 630 g

Mastering Prompt Engineering: Deep Insights for Optimizing Large Language Models (LLMs) is a comprehensive guide that takes readers on a journey through the world of Large Language Models (LLMs) and prompt engineering. Covering foundational concepts, advanced techniques, ethical considerations, and real-world case studies, this book equips both novices and experts to navigate the complex LLM landscape. It provides insights into LLM architecture, training, and prompt engineering methods, while addressing ethical concerns such as bias and privacy. Real-world case studies showcase the practical application of prompt engineering in a wide range of settings. This resource is not just for specialists but is a practical and ethically conscious guide for AI practitioners, students, scientific researchers, and anyone interested in harnessing the potential of LLMs in natural language processing and generation. Mastering Prompt Engineering serves as a gateway to a deeper understanding of LLMs and their responsible and effective utilization through its comprehensive, ethical, and practical approach.

Autoren/Hrsg.

Nayyar, Anand

Vairamani, Ajantha Devi

Kaswan, Kuldeep

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering

Inhaltsverzeichnis

1. Basic Insights into Large Language Models
2. Foundations of LLM-based Prompt Engineering
3. Familiarity with Prompt Design
4. Pre-processing and Tokenization in Prompt Engineering
5. State-of-the-Art Techniques in Prompt Engineering
6. Diverse Prompt Engineering Models and their Implementations
7. Evaluation and Refinement of Prompt Engineering
8. Prompt Engineering: Ethical Considerations and Challenges
9. Case Studies in Prompt Engineering
10. Future Trends in Large Language Models and Prompt Engineering cum Concluding Remarks

Über Autor(innen)

Kaswan, Kuldeep
Dr. Kuldeep Singh Kaswan is a Professor in the School of Computing Science and Engineering and Associate Dean–Planning at Galgotias University, Uttar Pradesh, India. He is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE). With more than thirteen years of academic, research, and administrative experience, his expertise spans brain–computer interfaces, cyborg technology, intelligent systems, and sustainability. He also specializes in institutional benchmarking and strategic planning, particularly for the QS World University Rankings and Times Higher Education (THE) World University Rankings. Dr. Kaswan holds a Ph.D. in Computer Science from Banasthali Vidyapith, Rajasthan, and a Doctor of Engineering from the Dana Brain Health Institute, Iran. He previously served at Amity University, Gautam Buddha University, and PDM University. An accomplished educator, researcher, administrator, and mentor, he has guided numerous undergraduate and postgraduate projects, and six doctoral scholars have successfully completed their Ph.D. degrees under his supervision. He has authored 22 books, contributed more than 100 book chapters, and published research in reputed journals and conference proceedings, advancing computing education, sustainability, institutional excellence, and interdisciplinary technological research.

Vairamani, Ajantha Devi
Dr. Ajantha Devi Vairamani is a distinguished Research Head at AP3 Solutions in Chennai, India and is a prominent figure in computer science and artificial intelligence. With a PhD from the University of Madras in 2015, she has played pivotal roles in UGC Major Research Projects and holds prestigious certifications from Microsoft Corp. Her academic prowess is evident in over 50 published papers and numerous books in computer science. Actively participating in international conferences, she contributes to research collaboration in various roles. Dr. Ajantha Devi's groundbreaking work in artificial intelligence, machine learning, and deep learning has led to Australian Patents. Her research spans Image Processing, Signal Processing, Pattern Matching, and Natural Language Processing, addressing real-world challenges. Her dedication has earned her Best Paper Presentation Awards and international honors, solidifying her position as a leading figure in the field, influencing both academia and industry.

Nayyar, Anand
Dr. Anand Nayyar is Professor in the School of Computer Science and Artificial Intelligence at Duy Tan University, Vietnam, where he serves as Vice-Chairman (Research) and Director of the IoT and Intelligent Systems Laboratory. His research interests include wireless sensor networks, Internet of Things, artificial intelligence, swarm intelligence, cloud computing, blockchain, cybersecurity, healthcare informatics, big data, drones, and wireless communications. He has published extensively in peer-reviewed journals, conference proceedings, book chapters, and scholarly books, and is an inventor with patents and copyrights in multiple jurisdictions. Dr. Nayyar is actively engaged in international research collaborations, research-funded projects, and postgraduate supervision. He serves on editorial boards and technical committees for international journals and conferences and contributes extensively to peer review and research evaluation activities. He is a Senior Member of IEEE and ACM.