Learn to write precise, effective prompts for any LLM — from GPT to Claude.
A hands-on skill covering the full spectrum of prompt engineering: anatomy of a good prompt, chain-of-thought reasoning, system instructions, few-shot patterns, and iterative refinement techniques.
Understand the building blocks: role, context, instruction, format, and constraints.
Every effective prompt has five components. Learn to identify and tune each one independently to get predictable, high-quality outputs from any model.
Make models show their work — and get dramatically better answers.
CoT prompting, zero-shot vs few-shot, self-consistency, and tree-of-thought: when to use each and how to combine them for complex reasoning tasks.
Write system instructions that shape model behavior reliably across sessions.
Persona, tone, guardrails, and output format — define them in the system prompt so every conversation starts from the right baseline without repeating yourself.
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