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Prompt with Clarity - The CAC Framework

Mark Ondash
CPTD®, Master Performance Consultant™

Master the art of data-driven prompting in this fast-moving, practical course built specifically for QuaerisAI users. You’ll learn how to transform fuzzy questions into precise, structured prompts using the CAC Framework—Context, Action, Constraint. Through guided examples and real-world scenarios, you’ll see how the right phrasing unlocks better answers, faster decisions, and fewer frustrating misfires. You won’t just learn what to do—you’ll get to practice. From comparing quarters to filtering by logic or percentages, this course walks you through the kinds of prompts you actually use at work. You’ll build fluency, test strategies, and leave with patterns you can reuse in any business context. By the end, you’ll be ready to prompt smarter, work faster, and get clearer insights from Quaeris every time.

What's included?

  • Real-world scenarios and prompting challenge
  • Downloadable frameworks and tip sheets
  • Self-assessments and reflection journals
  • Certificate of Completion

The LLMs

You’ll gain a clear understanding of how small language models (SLMs) work and why prompt quality matters. Learn how SLMs process, predict, and generate responses—and how to guide them effectively.

Personal brand

We guarantee you an exceptional experience with flexible learning paths and professional guidance

CAC 3 Part Framework

Discover a 3-part prompting framework that helps you structure inputs for clarity, context, and better results. Learn how each step enhances the AI’s response quality and aligns output with your goals.

Assignments

We will check your deliverables and grade your performance

Discuss with others

Participate in our online forum, share thoughts and ideas, increase connection, get help with your studies

10% discount (value up to $898)

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Course reviews

Mark M.

The AI Prompting Essentials course is an excellent resource for anyone who  is looking to get a basic understanding of how LLMs work, and how to maximize output by mastering prompts"