Beginner
7h · 34 lessons
Prompt Engineering Mastery
Patterns, evals, and prompt ops for real products.
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About this course
Move beyond tricks — build a repeatable prompt-engineering practice with evaluations and versioning.
What you'll learn
- Write prompts that are precise, testable and maintainable
- Apply the right technique — few-shot, CoT, structured output — per task
- Version and evaluate prompts like code
- Debug bad outputs systematically instead of guessing
Requirements
- Basic familiarity with an LLM chat interface
- Any programming language for the exercises
- An API key for at least one frontier model
Curriculum
6 modules · 24 lessons
Module 1Principles4 lessons
Module 1
Principles
- 01.01How LLMs read prompts
- 01.02Specificity and constraints
- 01.03The role of examples
- 01.04Anti-patterns to unlearn
Module quiz · 3 questions
Module 2Core techniques4 lessons
Module 2
Core techniques
- 02.01Few-shot done right
- 02.02Chain-of-thought and variants
- 02.03Self-critique loops
- 02.04Structured output with schemas
Module quiz · 3 questions
Module 3System design4 lessons
Module 3
System design
Module quiz · 3 questions
Module 4Evaluation4 lessons
Module 4
Evaluation
- 04.01Building a prompt eval set
- 04.02A/B testing prompts
- 04.03Regression tests
- 04.04Cost vs quality tradeoffs
Module quiz · 3 questions
Module 5Advanced4 lessons
Module 5
Advanced
- 05.01Multi-model routing
- 05.02Tool-use prompts
- 05.03Multimodal prompting
- 05.04Jailbreak-resistant prompts
Module quiz · 3 questions
Module 6Capstone4 lessons
Module 6
Capstone
- 06.01Rewrite a real prompt end-to-end
- 06.02Evaluate the improvement
- 06.03Document the prompt
- 06.04Peer review
Module quiz · 3 questions