Description

Understand LLM foundations and how they integrate with the MLOps ecosystem.
● Build robust prompt strategies, LLM chains, and RAG pipelines for complex workflows.
● Design and deploy AI agents and autonomous LLM-driven systems.
● Serve, scale, monitor, and evaluate LLMs across cloud and on-prem environments.

Who is This Book For?
This book is tailored for GenAI Developers, Machine Learning Engineers, and Data Scientists who want to build, deploy, and manage LLM-powered systems at scale. Readers should have foundational knowledge of AI/ML concepts, basic NLP familiarity, and experience with Python programming to fully benefit from the content.

Table of Contents
1. Unveiling the World of Large Language Models
2. Getting Started with MLOps
3. Mastering Prompt Management for LLMs
4. The Power of LLM Chaining
5. Retrieval Augmentation Generation
6. AI Agents and Autonomous Systems
7. Deploying Large Language Models
8. Model Monitoring and Evaluation
9. LLM Fine-tuning and Adaptation
10. LLM Security, Privacy, and Drift Detection
11. LLMOps with Langfuse