Beginner–Intermediate · 4 modules · 12 lessons
Prompting
Explore Prompting through 4 modules and 12 approachable lessons, with examples, practice, feedback, and a final hands-on project.
Written and edited by . Updated 2026-08-24.
What you will learn
- Structure goals, context, examples, constraints, and output formats.
- Break complex work into reliable multi-step prompt workflows.
- Test prompts for quality, safety, privacy, and repeatability.
Course outline
Module 01
How Models Read Instructions
Understand how tokens, context, ambiguity, and reliability limits affect a model's response.
- Tokens and Context · 12 minutes
- Ambiguity · 16 minutes
- Capability and Reliability · 20 minutes
Practice output: Prompt diagnosis notes
Module 02
Anatomy of a Strong Prompt
Set the goal, context, examples, constraints, and output format so the instruction is easier to follow.
- Goals and Context · 12 minutes
- Examples and Constraints · 16 minutes
- Output Structure · 20 minutes
Practice output: Prompt pattern set
Module 03
Advanced Prompt Workflows
Break down complex work, ask the model to critique its output, use sources, and add tools where they help.
- Task Decomposition · 12 minutes
- Critique and Revision · 16 minutes
- Retrieval and Tools · 20 minutes
Practice output: Prompt workflow
Module 04
Evaluation, Safety, and Reuse
Test prompts, protect data, resist instructions hidden in external content, and record each version change.
- Rubrics and Test Sets · 12 minutes
- Prompt Injection and Privacy · 16 minutes
- Versioning · 20 minutes
Practice output: Prompt and evaluation playbook
