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decodingai-magazine/llm-twin-course

A free, hands-on course to build a production-ready LLM & RAG system, including a personalized AI replica, applying LLMOps best practices.

Core Features

End-to-end development of production-grade LLM and RAG systems.

Implementation of LLMOps best practices for experiment tracking, model versioning, and prompt monitoring.

Guidance on building a personalized 'LLM Twin' that mimics an individual's writing style.

Architectural design using four Python microservices for data, features, training, and inference.

Integration with leading MLOps tools and cloud platforms like AWS SageMaker, Comet ML, and Qdrant.

Detailed Introduction

The LLM Twin Course is a comprehensive, free educational program designed to empower developers and ML engineers to build and deploy production-ready Large Language Model (LLM) and Retrieval-Augmented Generation (RAG) systems. It focuses on creating a unique 'LLM Twin' – an AI character capable of replicating an individual's writing style and personality. The curriculum spans the entire MLOps lifecycle, from data collection and feature engineering to LLM fine-tuning, scalable deployment via microservices, and robust monitoring, emphasizing industry best practices and integration with modern MLOps tools and cloud infrastructure.