LLM Engineer's Handbook: Master the art of engineering large language models from concept to production
Paul Iusztin
Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG
Louis-François Bouchard
Prompt Engineering for LLMs: The Art and Science of Building Large Language Model–Based Applications
John Berryman
Juan Farin: An LLM Awakens
Moshe Sipper
GPT-3: Building Innovative NLP Products using LLMs
Sandra Kublik
LangChain Crash Course: Build OpenAI LLM powered Apps: Fast track to building OpenAI LLM powered Apps using Python
Greg Lim
The Agentic AI Bible: The Complete and Up-to-Date Guide to Design, Develop, and Scale Goal-Driven, LLM-Powered Agents that Think, Execute and Evolve
Thomas R. Caldwell
Quick Start Guide to Large Language Models: Strategies and Best Practices for Using ChatGPT and Other LLMs
Sinan Ozdemir
Building AI Agents with LLMs, RAG, and Knowledge Graphs: A practical guide to autonomous and modern AI agents
Salvatore Raieli
Ollama Crash Course: Build Local LLM powered Apps
Greg Lim
LLMs in Production: From language models to successful products
Christopher Brousseau
Learning LangChain: Building AI and LLM Applications with LangChain and LangGraph
Mayo Oshin
Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
Ben Auffarth
Universal's Guide to LL.M. Entrance Examination, Including Previous Years Solved Papers
Gaurav Mehta
Designing Large Language Model Applications: A Holistic Approach to LLMs
Suhas Pai
Agentic AI Engineering: Systems That Reason and Act Autonomously – Designing, Building, and Prompting LLM-Based Agents for Real-World Deployment
Hyun Erwin
Building LLM Powered Applications: Create intelligent apps and agents with large language models
Valentina Alto
Knowledge Graphs and LLMs in Action: Build AI systems using connected data
Alessandro Negro
LL.M. Roadmap: An International Students Guide to U.S. Law School Programs
George E. Edwards
AI Prompt Engineering: Foundations of Communication with LLMs – Building Generative AI and Agentic AI Prompt Systems Across Development, Testing, and Deployment (AI Engineering)
Nelson Ming