Textbooks

The two textbooks recommended for this class were chosen for their complementary focus on both theoretical foundations and practical applications of large language models (LLMs) in real-world scenarios.

Alammar and Grootendorst’s book provides a clear and accessible exploration of transformer architectures, fine-tuning techniques, and generative AI workflows, making it ideal for understanding the core principles of LLMs. Huang’s guide, on the other hand, emphasizes actionable strategies for deploying AI systems in production, including prompt engineering, retrieval-augmented generation, and cost-effective optimization.

Together, these resources provide a balanced perspective on both the conceptual underpinnings and the practical challenges of working with modern AI technologies.

1. Jay Alammar, Maarten Grootendorst, Hands-On Large Language Models: Language Understand- ing and Generation, 1st ed., Published by O’Reilly Media, Inc., ISBN-13 978-1098150969.
   This books is available in print and digital on O’Reilly Media.
   GSU Library Link (Requires active GSU student/faculty/staff account)

2. Ken Huang, Practical Guide for AI Engineers, Independently published (May 18, 2024), ISBN-13 979-8325962455.
   This book is available in print and digital on Kindle (Unlimited).