Prompt Engineering for Improved Performance
Your prompts are leaving performance on the table. This 55-minute course teaches you the precise techniques to extract maximum capability from generative AI models, turning vague requests into razor-sharp outputs that actually deliver business value.
AIU.ac Verdict: Ideal for developers, product managers, and AI practitioners who need immediate, practical wins with LLMs—no theory bloat. The main limitation: this is a sprint, not a deep dive, so you’ll want supplementary practice to truly master advanced prompt patterns.
What This Course Covers
You’ll learn the mechanics of how generative AI interprets instructions, then move straight into high-impact techniques: prompt structure, context framing, temperature and parameter tuning, and iterative refinement workflows. Kesha walks through real-world scenarios where small prompt adjustments yield dramatically better outputs—cost savings, accuracy gains, and reduced hallucinations.
The course emphasises hands-on application over abstract concepts. You’ll work through Pluralsight’s sandboxes to test prompts live, see failure modes, and understand why certain framings work whilst others don’t. By the end, you’ll have a repeatable system for diagnosing and fixing underperforming AI interactions in your own projects.
Who Is This Course For?
Ideal for:
- Software engineers integrating LLMs: Need practical techniques to improve API outputs without re-engineering architecture
- Product and data teams: Want to squeeze better results from ChatGPT, Claude, or internal models without waiting for model upgrades
- AI-curious professionals: New to generative AI but need actionable skills immediately—no prerequisite knowledge required
May not suit:
- Researchers seeking theoretical depth: This is applied, not academic—no coverage of transformer architecture or training methodologies
- Learners with limited time: 55 minutes is tight; you’ll need follow-up practice to internalise techniques beyond the course
Frequently Asked Questions
How long does Prompt Engineering for Improved Performance take?
55 minutes. It’s designed as a focused sprint, not a semester-long commitment—perfect for busy professionals.
Do I need prior AI or coding experience?
No. The course assumes you’ve used a generative AI tool (like ChatGPT) but doesn’t require technical background. Developers will extract more, but it’s accessible to non-technical roles too.
Will I get hands-on practice?
Yes. Pluralsight includes sandboxes and labs where you’ll test prompts live and see results immediately—not just video lectures.
Who is Kesha Williams?
A Pluralsight-vetted expert author (top 5.5% acceptance rate). She specialises in practical AI skills and has built courses trusted by Fortune 500 companies.
Course by Kesha Williams on Pluralsight. Duration: 0h 55m. Last verified by AIU.ac: March 2026.
