Prompt EngineeringCourse

Generative AI and Agents / 5 weeks

Prompt Engineering

Teaches practitioners how to write prompts that get reliable, structured, grounded output from LLMs and how to evaluate prompts as the product surface they are.

Learning path

Six modules with practical application.

  1. Role, instruction, constraints, context, examples, and output format that turn an LLM into a reliable component
  2. Selecting, ordering, and using examples to teach the model the pattern it needs to follow
  3. Asking the model to reason explicitly when the task benefits, and skipping it when speed and brevity matter
  4. Forcing the model to return JSON, function calls, or specific schemas so downstream code can rely on its output
  5. Treating prompts like code: a versioned change with an evaluation set, a measurement, and a decision
  6. Defending prompts against injection, jailbreaks, sensitive content, and tool misuse

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