NVIDIA DLI–Building LLM Applications with Prompt Engineering

FAQ–Frequently asked questions about the NVIDIA DLI LLM Applications with Prompt Engineering Training What is prompt engineering with LLMs?

Prompt engineering is the practice of designing, structuring and iterating prompts to reliably obtain the desired behaviour from an LLM (GPT, LLaMA, Mistral, etc.), without retraining the model.

What is the difference between prompt engineering, fine-tuning and RAG?

Prompt engineering only changes the instruction sent to the model (low cost, fast iteration). RAG adds retrieval from external documents at query time. Fine-tuning retrains the model on specific data (highest cost and effort). This training focuses on prompt engineering.

Which tools and frameworks are covered?

LLM APIs (including NVIDIA NeMo and major models), LangChain for orchestration (chains, agents, tools), and supporting tooling to build chatbots, pipelines and structured-extraction applications.

How long is this NVIDIA DLI training at MFE-IT?

The training lasts 1 day (7 hours), remote with recorded sessions or on-site, ending with the assessment for the NVIDIA DLI certificate.

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Good to know

Our sessions are guaranteed from a single registrant, with no risk of postponement (except in cases of force majeure). A prior interview takes place between the participant and a company representative to fully take into account the participant’s profile (level, needs, professional context, challenges, etc.). Evaluation: during the training, the trainer assesses participants’ learning progress through quizzes, role-plays and practical exercises. Participants receive a certificate of achievement at the end of the training. This training is part of our Artificial Intelligence training catalogue.

Objectives of the NVIDIA DLI LLM Applications with Prompt Engineering Training

• By the end of this training:
• Understand how LLMs work and their generative capabilities.
• Master prompt-engineering techniques: zero-shot, few-shot, chain-of-thought.
• Use LLM APIs to build applications.
• Design pipelines with LangChain and orchestration tools.
• Create chatbots and intelligent assistants.
• Apply security and reliability best practices.

Prerequisites for the NVIDIA DLI LLM Applications with Prompt Engineering Training

Python programming experience (intermediate level). Basic notions of AI and NLP recommended. No specific prior LLM experience required.

Target audience of the NVIDIA DLI LLM Applications with Prompt Engineering Training

Developers wanting to integrate LLMs into their applications. Data scientists and AI engineers. Solution architects evaluating generative AI. Technical project managers leading AI initiatives.