Generative AI: Prompt Engineering Basics

What you'll learn

• Explain how large language models generate text and recognize common failure modes
• Design clear, role-based prompts and system instructions for consistent outputs
• Supply context and grounding using retrieval and multimodal inputs
• Apply zero-, one-, and few-shot prompting patterns to steer behavior
• Structure outputs and formats with templates, constraints, and validators
• Use reasoning and decomposition techniques to solve complex tasks
• Iterate, test, and debug prompts with systematic experiments
• Define and apply evaluation metrics for prompt quality and reliability
• Implement safety, ethics, and risk mitigation strategies in prompts
• Integrate tools, functions, agentic workflows, and RAG pipelines

Prerequisites

No advanced ML knowledge required; basic programming familiarity and experience using web-based LLMs or APIs is recommended.

Skills you'll gain

• Prompt design
• LLM behavior analysis
• Context engineering
• Few-shot learning
• Output formatting & templating
• Reasoning and decomposition
• Prompt testing & debugging
• Evaluation and metrics
• Safety & ethical risk mitigation
• Tool and agent integration
• Retrieval-augmented generation (RAG)
• Multimodal prompting