Intermediate · 5 modules · 15 lessons
Applied AI
Explore Applied AI through 5 modules and 15 approachable lessons, with examples, practice, feedback, and a final hands-on project.
Written and edited by . Updated 2026-08-24.
What you will learn
- Identify AI opportunities from real tasks and user needs.
- Design a human–AI workflow with clear inputs, outputs, and ownership.
- Prototype and evaluate an AI-assisted process with safeguards.
Course outline
Module 01
From Work to AI Opportunities
Find recurring tasks worth improving by starting with the problem, not the tool.
- Task Inventory · 12 minutes
- Pain, Frequency, and Value · 16 minutes
- When Not to Use AI · 20 minutes
Practice output: Opportunity shortlist
Module 02
Choosing an Approach
Compare simple rules, predictive AI, and generative AI, then decide whether to build or use an existing service.
- Rules, Prediction, or Generation · 12 minutes
- Build, Buy, or Combine · 16 minutes
- Data Readiness · 20 minutes
Practice output: Solution approach memo
Module 03
Designing the Workflow
Break a process into steps, then define context, data flow, tools, and human handoffs.
- Workflow Decomposition · 12 minutes
- Context and Data Flow · 16 minutes
- Tools and Handoffs · 20 minutes
Practice output: Workflow blueprint
Module 04
Testing Quality
Prepare reference examples, a rubric, a baseline, and error analysis before wider use.
- Golden Sets and Rubrics · 12 minutes
- Error Analysis · 16 minutes
- Cost and Latency · 20 minutes
Practice output: Evaluation scorecard
Module 05
Building a Safer Prototype
Combine a prototype with fallbacks, monitoring, and a staged rollout so failures remain manageable.
- Human Review and Fallbacks · 12 minutes
- Monitoring · 16 minutes
- Staged Rollout · 20 minutes
Practice output: Working AI workflow prototype
