LLM Engineer's Handbook
Master the art of engineering large language models from concept to production
Created by Paul Iusztin, Maxime Labonne
Explore the full process of building, training, and deploying large language models with a focus on practical, production-ready solutions. You'll gain hands-on experience in data engineering, fine-tuning, and deploying LLMs that are scalable and efficient.
Packt | Oct 2024 | 522 min
What You Will Learn
You will learn by working through a practical example that demonstrates each step, from preparing data to deploying a full LLM system. The approach combines clear explanations with hands-on guidance, helping you apply advanced techniques directly to your own projects.
Key Features
- Build and refine large language models using real-world data and fine-tuning methods
- Deploy and monitor LLMs for reliable, high-performance production use
- Apply preference alignment and inference optimization to improve model results
Target Audience
Designed for AI engineers, NLP professionals, and those with a basic understanding of LLMs, Python, and AWS. If you want to deepen your knowledge and confidently build production-grade LLM applications, this course will help you achieve your goals.
