Prompt Engineering Training
Prompt engineering training builds the technical craft of designing prompts that produce precise, reliable, reproducible results from large language models. This is the deep, build-it track, not casual ChatGPT use, but the discipline of structuring instructions, chaining steps, grounding outputs in your own data with RAG, and evaluating quality. Learni delivers it hands-on across ChatGPT, Claude, and other LLMs, remote-first in your time zone, with onsite available on request.
What is prompt engineering, as a discipline?
Prompt engineering is the practice of engineering the input to a language model so the output is accurate, structured, and repeatable, every time, not just once. It sits between casual usage and full application development: the people who do it well can turn an unreliable model into a dependable component of a workflow or product. This program is for those building something on top of LLMs, an internal assistant, a content pipeline, a document-analysis tool, where consistency and quality actually matter.
Why structured prompting changes the outcome
The difference between a vague question and a well-engineered prompt is the difference between a demo and a production tool. Techniques like few-shot examples, chain-of-thought, and explicit output schemas turn unpredictable responses into ones you can parse, test, and trust, which is what makes an LLM usable inside real software and processes.
What's covered: techniques and craft
The curriculum moves from core technique to building reliable, grounded systems. It is hands-on throughout, with your own use cases as the proving ground.
- Zero-shot, few-shot, and example selection
- Chain-of-thought and step-by-step reasoning
- Role and persona design for consistent behavior
- Structured output: schemas, JSON, and parseable formats
- Prompt chaining and multi-step workflows
- Retrieval-augmented generation (RAG): grounding answers in your data
- Evaluation: testing prompts and reducing hallucination
- Building reusable, version-controlled prompt libraries
RAG and grounding in your own data
The most valuable enterprise use of LLMs is answering questions from your own documents, policies, knowledge bases, and product data, rather than the open internet. We dedicate real time to retrieval-augmented generation: how to feed relevant context into a prompt, how to keep answers grounded and citable, and how to evaluate whether the system is actually using your sources. This is the bridge from clever prompts to a tool your organization can rely on.
Who it's for and what they can do after
Built for developers, AI builders, technical product managers, and analysts who are building on LLMs. After the program, participants can design reliable prompts, structure multi-step workflows, ground outputs in your data with RAG, and evaluate prompt quality systematically rather than by trial and error. Some Python familiarity helps for the RAG modules but is not required for the core craft.
Formats and how it's billed
The program runs as a hands-on live cohort, remote-first in your time zone, with onsite available on request, and is sized to how deep into RAG and tooling your team needs to go. It is billed directly to your L&D budget: USD invoicing, W-9 available on request, no public funding. You get one clear quote per cohort with contracting handled for you.
Is prompt engineering a real job?
Yes, prompt engineering is recognized as a full-fledged professional skill. Many companies hire prompt engineers to optimize their AI usage. It's also a cross-functional skill valued in all professions.
Do you need to know how to code to do prompt engineering?
No, prompt engineering is accessible to everyone. It's primarily about structuring your thinking and communicating effectively with an AI. No programming skills are required.
Which tools are covered in the training?
We mainly work on ChatGPT (OpenAI) and Claude (Anthropic), with demonstrations on Midjourney and Stable Diffusion for image AI. The techniques taught are transferable to any LLM.
How is the prompt engineering program billed?
The program is billed directly to your L&D budget. USD invoicing, W-9 available on request, no public funding. You get one clear quote per cohort with contracting handled for you.
What level do you reach after the program?
After 2 days, your team masters advanced prompting techniques and can build complex AI workflows. Each participant leaves with a library of ready-to-use prompt templates.
AI Training: Master Artificial Intelligence
AI training builds a shared, practical understanding of artificial intelligence across your whole team, so people know what these tools can and cannot do before they rely on them. This is foundational AI literacy: what models are, where they help, where they fail, and how to use them responsibly at work. Learni delivers it as a live cohort led by a practitioner, remote-first in your time zone, with onsite available on request.
AI Training for Business
AI training for business focuses on one thing: turning AI into measurable outcomes inside your actual workflows. This is the applied track, not AI theory and not a coding course, but the work of identifying high-value use cases, redesigning a process around them, and proving the return. Learni delivers it as a custom cohort built on your processes, remote-first in your time zone, with onsite available on request.
ChatGPT Training for Business
ChatGPT training for business turns a tool your team already opens into a real productivity gain on everyday work, writing, summarizing, analyzing, and drafting, done faster and better. This is the practical, non-developer track: it teaches the people doing the work how to get reliable results, safely, without touching code. Learni delivers it as a hands-on cohort on your real tasks, remote-first in your time zone, with onsite available on request.
Let's build
your next
program.
30 minutes with a learning advisor. No commitment. No sales pitch dressed up as a demo.