Cover image for LLM Design Patterns

LLM Design Patterns

A Practical Guide to Building Robust and Efficient AI Systems

Ken Huang

Created by Ken Huang

Discover how to build robust and efficient AI systems using proven design patterns for large language models. Gain hands-on experience with every stage of the LLM lifecycle, from data preparation to advanced prompting and model optimization. Develop skills that help you create scalable and reliable language models for real-world applications.

Packt | May 2025 | 538 min

What You Will Learn

You will work through practical examples and real-world scenarios that illustrate each phase of LLM development. By applying reusable design patterns, you will learn to address common challenges and implement effective solutions. The structured approach helps you build confidence as you progress from foundational techniques to advanced strategies in LLM deployment.

Key Features

  • Master data preparation, training pipelines, and model optimization for LLMs
  • Apply advanced prompting and retrieval techniques to enhance model capabilities
  • Evaluate, interpret, and ensure fairness in language models for trustworthy results

Target Audience

Designed for AI engineers, data scientists, and software developers with a solid grasp of machine learning and Python. If you are responsible for developing or deploying language model-powered systems and want to deepen your expertise in building scalable, efficient, and fair AI solutions, this course is a great fit.

Related courses

Cover image for AI Chatbot with Apple Foundation Models, SwiftUI, and SwiftData
Cover image for Build an AI-Powered Goals App with Foundation Models in SwiftUI, iOS 26, and SwiftData
Cover image for OpenClaw for Developers: Create Your First AI Agent
Cover image for Claude Code Essentials: Your First AI-Assisted Coding Workflow
Cover image for Retrieval-Augmented Generation (RAG) for AI Engineers - Build Production-Ready Applications
Cover image for Applied Context Engineering for RAG & LLM Systems