Prompt Engineering Masterclass
Write prompts that reliably get the outputs you need from GPT-4, Claude, and Gemini.
About this course
The practical guide to getting results from large language models. You will learn proven prompt patterns, chain-of-thought reasoning, few-shot learning, and how to build structured pipelines using LLM APIs. Exercises cover writing, coding, research, data extraction, and content generation use cases.
Target audience: Marketers, writers, developers, product managers, anyone using AI tools daily
What you will learn
- Prompt engineering
- LLM APIs
- Chain-of-thought reasoning
- Structured output
- AI workflow design
Course syllabus
10 modules · video + exercises
- 1How LLMs work: tokens, context windows, and temperature
- 2Core prompt anatomy: role, context, task, format, constraints
- 3Zero-shot and few-shot prompting
- 4Chain-of-thought and step-by-step reasoning
- 5Role prompting and persona design
- 6Structured output: JSON mode and function calling
- 7Retrieval-augmented prompting (RAG basics)
- 8Prompt evaluation and iteration methodology
- 9Building a prompt library for your workflow
- 10Capstone: build an AI writing assistant
Frequently asked questions
Which AI models does this cover?
The course covers GPT-4o (OpenAI), Claude 3 and 4 (Anthropic), and Gemini Pro (Google). The principles apply to any instruction-following LLM.
Is this relevant if I am not a developer?
Yes. More than half the course is about non-code workflows — writing, research, data extraction, and content generation. No programming is required for those sections.
Ready to start Prompt Engineering Masterclass?
Join 9,800+ learners already enrolled. Self-paced, certificate on completion.