Prompt Engineering Best Practices
Generative AI adoption is accelerating—and your prompts determine your output quality. This course cuts through the noise to teach you battle-tested techniques that separate mediocre results from exceptional ones. In 84 minutes, you’ll learn exactly how to structure, refine, and optimise prompts across real-world scenarios.
AIU.ac Verdict: Ideal for developers, product managers, and AI practitioners who need immediate, actionable prompt strategies without the fluff. The course is concise and practical, though it assumes basic familiarity with generative AI concepts—complete beginners may benefit from foundational context first.
What This Course Covers
You’ll explore prompt structure fundamentals, including context-setting, instruction clarity, and output formatting. The course covers iterative refinement techniques, prompt chaining for complex tasks, and how to avoid common pitfalls like hallucination and vague responses. Expect hands-on examples across use cases: content generation, code assistance, and data analysis.
Mohamed Echout walks you through real-world patterns: few-shot prompting, role-based prompts, and temperature/parameter tuning. You’ll learn why certain phrasings trigger better model behaviour, how to test prompts systematically, and when to escalate to fine-tuning. The practical labs let you experiment immediately, so you leave with a mental model you can apply on day one.
Who Is This Course For?
Ideal for:
- Software developers integrating LLMs: You’ll learn prompt patterns that improve code generation quality and reduce iteration cycles with AI assistants.
- Product managers and business analysts: Understand how to brief AI tools effectively and evaluate AI-generated outputs critically for your roadmap.
- Data professionals and analysts: Master prompts for data extraction, transformation, and insight generation—turning raw LLM output into business value.
May not suit:
- Complete AI novices: This assumes you’ve interacted with ChatGPT or similar tools. If you’re new to generative AI entirely, start with foundational courses first.
- Machine learning engineers focused on model training: This course is about using models, not building them. If you’re training custom LLMs, you’ll need deeper technical content.
Frequently Asked Questions
How long does Prompt Engineering Best Practices take?
The course is 1 hour 24 minutes (84 minutes). Most learners complete it in one sitting or across two focused sessions.
Do I need coding experience?
No. Whilst examples include code prompts, the principles apply equally to non-technical use cases. Basic familiarity with generative AI tools (like ChatGPT) is more important than coding skills.
Will this course teach me to fine-tune or train models?
No. This course focuses on prompt optimisation—getting the best results from existing models. Fine-tuning and training are separate, advanced topics.
Is this course vendor-specific (OpenAI, Anthropic, etc.)?
The principles are model-agnostic, though examples may reference popular platforms. Best practices translate across ChatGPT, Claude, Gemini, and other LLMs.
Course by Mohamed Echout on Pluralsight. Duration: 1h 24m. Last verified by AIU.ac: March 2026.
