What you’ll learn
- Write bounded instructions with context and output requirements.
- Check generated material against supplied evidence.
- Recognize privacy, reliability and task-suitability limitations.
Proposed course content
6 sections · 13 illustrative lesson records
Capabilities and limitations3 lessons
- Introduction to Practical Generative AI & Prompt Engineering
Explore clear task instructions, structured outputs and evidence checks for generative AI using non-sensitive examples and explicit human review.
Public introduction · Video not supplied - Distinguish generated content from verified evidence
Distinguish generated content from verified evidence. Module: Capabilities and limitations.
Enroll to access · Video not supplied - Choose tasks appropriate for human review
Choose tasks appropriate for human review. Module: Capabilities and limitations.
Enroll to access · Video not supplied
Clear instructions2 lessons
- State a task, relevant context and constraints
State a task, relevant context and constraints. Module: Clear instructions.
Enroll to access · Video not supplied - Use examples without including sensitive information
Use examples without including sensitive information. Module: Clear instructions.
Enroll to access · Video not supplied
Structured outputs2 lessons
- Request consistent formats and validate required fields
Request consistent formats and validate required fields. Module: Structured outputs.
Enroll to access · Video not supplied - Handle missing or contradictory answers
Handle missing or contradictory answers. Module: Structured outputs.
Enroll to access · Video not supplied
Grounding and verification2 lessons
- Provide source material and check factual claims
Provide source material and check factual claims. Module: Grounding and verification.
Enroll to access · Video not supplied - Require uncertainty and abstention when evidence is absent
Require uncertainty and abstention when evidence is absent. Module: Grounding and verification.
Enroll to access · Video not supplied
Iteration and comparison2 lessons
- Compare prompts on a small fixed test set
Compare prompts on a small fixed test set. Module: Iteration and comparison.
Enroll to access · Video not supplied - Record failures rather than selecting only favorable examples
Record failures rather than selecting only favorable examples. Module: Iteration and comparison.
Enroll to access · Video not supplied
Responsible workflows2 lessons
- Review outputs before sharing or taking action
Review outputs before sharing or taking action. Module: Responsible workflows.
Enroll to access · Video not supplied - Document privacy, authorship and academic-responsibility boundaries
Document privacy, authorship and academic-responsibility boundaries. Module: Responsible workflows.
Enroll to access · Video not supplied
Requirements
- Basic computer use and technical reading.
- A permitted model interface and non-sensitive or synthetic examples.
Tools and resources
- A development computer with resources appropriate to the proposed local exercises.
- A permitted generative model interface and synthetic source notes.
- A document editor or notebook and a simple output-validation checklist.
Description
Explore clear task instructions, structured outputs and evidence checks for generative AI using non-sensitive examples and explicit human review.
Who this course is for
Learners beginning responsible use of generative AI in practical tasks.
Example practical project
Proposed capstone: a human-reviewed assistant that summarizes synthetic meeting notes into a validated task list with source references.