Advanced Prompt Engineering
LLM outputs are only as good as your prompts—and most teams are leaving performance on the table. This course teaches you the advanced techniques that separate mediocre results from production-grade AI outputs, covering prompt structuring, chain-of-thought reasoning, and real-world optimisation patterns you’ll use immediately.
AIU.ac Verdict: Ideal for AI engineers, product managers, and developers already working with LLMs who want to move beyond basic prompting. Best suited to those with foundational GenAI knowledge; assumes you’re past ‘hello world’ and ready for nuanced, measurable improvements.
What This Course Covers
You’ll explore systematic prompt design principles, including role-based prompting, few-shot learning, and structured output formatting. The course covers advanced reasoning patterns like chain-of-thought, tree-of-thought, and multi-step decomposition—techniques that dramatically improve accuracy for complex tasks. Expect practical labs where you’ll refine prompts iteratively, measure performance improvements, and apply these patterns to real scenarios like code generation, content analysis, and decision support.
Maaike van Putten (one of Pluralsight’s elite 5.5% of accepted authors) grounds the theory in hands-on sandboxes where you’ll test edge cases, debug prompt failures, and optimise for both quality and cost. You’ll leave with a mental model for diagnosing why a prompt underperforms and a toolkit of proven techniques to fix it—directly applicable to production systems.
Who Is This Course For?
Ideal for:
- AI/ML Engineers: Already deploying LLMs; need systematic methods to improve output quality and consistency across applications.
- Product Managers in GenAI: Building LLM-powered features; require understanding of prompt optimisation to set realistic expectations and guide engineering.
- Data Scientists & Developers: Integrating LLMs into workflows; want to move beyond trial-and-error to reproducible, measurable prompt strategies.
May not suit:
- Complete GenAI Beginners: No grounding in how LLMs work or basic prompting concepts; start with foundational GenAI courses first.
- Non-Technical Stakeholders: Course assumes hands-on coding and experimentation; better suited to technical practitioners than business decision-makers.
Frequently Asked Questions
How long does Advanced Prompt Engineering take?
1 hour 31 minutes. Designed for focused, practical learning—you can complete it in one sitting or split across sessions.
What prior knowledge do I need?
Familiarity with LLMs (ChatGPT, Claude, etc.) and basic prompting. This course assumes you’ve moved past introductory concepts.
Are there hands-on labs?
Yes. Pluralsight’s sandboxes let you experiment with real prompts, test techniques, and see immediate results—no setup required.
Who is the instructor?
Maaike van Putten, a Pluralsight-certified expert author (top 5.5% of applicants). She brings production experience and practical insight.
Course by Maaike van Putten on Pluralsight. Duration: 1h 31m. Last verified by AIU.ac: March 2026.
