Ultimate LLM Engineering, RAG, QLoRA

About this course

Ultimate LLM Engineering, RAG & QLoRA is a comprehensive hands-on course designed to help you build, customize, and deploy modern Large Language Model applications from the ground up. Whether you are a developer, data scientist, AI engineer, or aspiring Generative AI professional, this course provides practical knowledge to work with LLMs and build real-world AI solutions.

You will begin by understanding the foundations of Large Language Models, Transformer architectures, tokenization, embeddings, attention mechanisms, prompting, inference, and model evaluation. The course then moves into practical LLM engineering concepts, including working with open-source models, model APIs, inference pipelines, context management, and production-oriented application development.

A major focus of the course is Retrieval-Augmented Generation (RAG). You will learn how to build intelligent applications that connect LLMs with external and private knowledge sources. You will explore document processing, chunking, embeddings, vector databases, semantic search, retrieval strategies, reranking, context construction, and RAG evaluation. You will also learn how to design reliable RAG pipelines capable of answering questions using your own documents and enterprise data.

The course also provides practical coverage of QLoRA and parameter-efficient fine-tuning. You will learn how quantization works, why QLoRA is useful, how to prepare datasets, configure fine-tuning workflows, train customized LLMs, evaluate results, and understand the trade-offs between full fine-tuning and parameter-efficient approaches.

Through practical projects and hands-on exercises, you will combine LLM engineering, RAG, embeddings, vector search, and QLoRA to create powerful Generative AI applications. By the end of the course, you will have the skills and practical understanding needed to design, customize, evaluate, and deploy modern LLM-powered applications.

This course is ideal for anyone who wants to move beyond basic prompt

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