OneRange Vero

Advanced Prompt Engineering

Learners master advanced prompting techniques for reliable, structured results. The course covers few-shot and chain-of-thought, structured output, system prompts and roles, and prompt chaining and templates. They finish able to engineer prompts that perform consistently at scale.

What this course covers

Learners master advanced prompting techniques for reliable, structured results. The course covers few-shot and chain-of-thought, structured output, system prompts and roles, and prompt chaining and templates. They finish able to engineer prompts that perform consistently at scale.

The course runs across 12 topics, each one a short adaptive session rather than a recorded lecture. The tutor explains the idea, works an example, checks understanding, and adjusts the next step to the answer given.

  • Introduction to System Prompts and Roles — Understand the role of system prompts in defining the AI's persona, boundaries, and behavioral rules.
  • Hands-on: Crafting System Personas — Practice writing and testing system prompts to enforce specific domain expertise and tone constraints directly in the tool.
  • Few-Shot Prompting Mechanics — Learn how to guide model behavior, style, and formatting through strategically chosen input-output examples.
  • Hands-on: Designing Few-Shot Exemplars — Build and refine a few-shot prompt in the tool to handle edge cases and maintain consistency.
  • Chain-of-Thought (CoT) Reasoning — Explore how eliciting step-by-step reasoning improves performance on complex logical and mathematical tasks.
  • Hands-on: Implementing CoT and Zero-Shot CoT — Apply Chain-of-Thought techniques in the tool to solve multi-step reasoning problems reliably.
  • Structuring Outputs (JSON and XML) — Techniques for forcing the model to return data in reliable, machine-readable structured formats.
  • Hands-on: Enforcing Structured Output Schemas — Write prompts that consistently output valid JSON matching a specific schema, and test them in the tool.
  • Dynamic Prompt Templates and Variables — How to design reusable prompt templates that accept dynamic input variables for scalable workflows.
  • Principles of Prompt Chaining — Deconstruct complex tasks into a sequence of smaller, targeted prompts to improve accuracy and handle larger scopes.
  • Hands-on: Building a Multi-Step Prompt Chain — Connect multiple prompts together in the tool, passing the output of one step as the input to the next.
  • Testing and Iterating Prompts at Scale — Methods for systematically evaluating prompt performance, identifying failure modes, and versioning changes.

Skills you build

Results are measured against named skills in the OneRange taxonomy of more than 10,000 skills, so a manager sees proficiency per skill rather than a completion tick. This course maps to Generative AI Concepts, Critical Thinking, Data Analysis, AI Ethics, Content Strategy.

  • Generative AI Concepts
  • Critical Thinking
  • Data Analysis
  • AI Ethics
  • Content Strategy

Who it is for

Power users, builders. The material is pitched at intermediate level, and takes roughly 150 minutes at a typical pace. Because every session adapts, someone who already knows a topic moves through it quickly instead of sitting through an explanation they do not need.

It sits in the Category: Prompting track of the Vero AI Catalog, and can be assigned to one person, a team, or the whole company.

How it is delivered and assessed

Delivery is conversational and interactive, including guided lab exercises. There is no video to sit through and no slide deck to click past.

Understanding is checked with a lab assessment of 5 items, with a pass mark of 70%.

Administrators can copy this course into their own library and adapt it — edit the outline, change the duration, swap the assessment format, or ground it in internal documentation so answers cite the company's own source material.

Related

Course code CAT-PRM.