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We're here to help you find itUnlock the potential of advanced LLM systems with our Building RAG Agents with LLMs (NVIDIA) course. This 16-hour intensive training provides insights into deploying agent systems powered by large language models. With a focus on practical application, you'll learn to design dialog management systems, leverage embeddings for efficient content retrieval, and implement RAG agents capable of answering questions from datasets without fine-tuning. Key topics include LLM inference interfaces, pipeline design, and working with documents. Equip yourself with the skills to effectively deploy scalable LLM systems that meet user and customer demands. Join us and transform your understanding of LLM capabilities!
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♱ Excluding VAT/GST
You can request classroom training in any city on any date by Requesting More Information
Minimum Required Prerequisites for Building RAG Agents with LLMs (NVIDIA)
To ensure a successful learning experience in the Building RAG Agents with LLMs (NVIDIA) course, we recommend that participants have the following foundational knowledge:
These prerequisites are designed to ensure that you can fully engage with the course material and maximize the value of your learning experience. If you meet these criteria, you're well on your way to building and deploying advanced LLM systems!
Introduction: The "Building RAG Agents with LLMs (NVIDIA)" course is ideal for professionals aiming to leverage state-of-the-art LLMs for advanced retrieval, dialog management, and scalable deployment solutions.
Target Audience and Job Roles:
The "Building RAG Agents with LLMs (NVIDIA)" course equips students with the skills to design, implement, and deploy sophisticated retrieval-augmented generation (RAG) agents using large language models (LLMs). Participants will gain hands-on experience in dialog management, document reasoning, and efficient content retrieval techniques.
