You buildAn agent workflow on your live pipeline
AI literacy, ethics and data compliance
Write the AI use policy your team will actually follow, put it in force with a review step, and measure how the decisions change.
Free
8 modules
4 weeks
Foundational
What you will learn
- Explain what these systems do and where their output needs a human.
- Classify the data your team handles and decide which tools may see it.
- Assess a use case for bias, transparency, accessibility and intellectual property.
- Run an intake, risk tiering and approval process people can follow.
- Place the EU AI Act, privacy principles and the NIST AI RMF against your own work.
- Finish with a governance pack: register, risk assessment, controls and an incident playbook.
Course content
Method step 1, Profile
What these systems do, what they do not, and how your team uses them today.
- What the systems do and do not do
- Probabilistic output and hallucination
- Record how your team uses AI today
- Where human reliance belongs
Method step 2, Build
Four tiers of data, and which tools each tier is allowed to reach.
- Public, internal, confidential, restricted
- Personal data and retention
- Vendor terms and prompt leakage
- Classify your own data
- The approved-tool decision
Method step 2, Build
The harms worth checking for, and how to check for them repeatably.
- Bias, fairness and human impact
- Transparency, explainability and accessibility
- Intellectual property and misinformation
- Assess one of your own use cases
Method step 2, Build
Intake to retirement, with a named owner at every gate.
- Use-case intake and risk tiering
- Owners and responsibilities
- Approval gates
- Build the model and vendor inventory
- Monitoring and retirement
Method step 2, Build
The EU AI Act, privacy principles and the NIST AI RMF against your own work.
- The EU AI Act, in the shape of your use cases
- Privacy principles
- The NIST AI risk management framework
- Where this material stops and counsel starts
Method step 3, Deploy
The policy goes into force. Putting it in force completes the course.
- Write the acceptable-use policy
- Human review and escalation
- Red teaming and audit evidence
- Employee training and third-party oversight
- Put it in force across the team
Method step 4, Measure
Six real decisions run against the policy you just wrote.
- Hiring and marketing content
- Customer support and education
- Finance and healthcare
- Measure the change in decisions
- The outcome sheet
Method step 5, Document
Everything above, assembled into one document a director can read.
- Assemble the register and classification
- User notice and the incident playbook
- Write the executive summary
- Publish it and book the review
Requirements
- Responsibility for how one team uses AI, and the standing to set a rule.
- A list of the tools your team uses today, however informal.
- About three hours a week for four weeks.
- A colleague who will review the policy with you.
About this course
This course is for whoever owns the answer to "are we allowed to use that": team leads, operations, HR and legal. It is written for the person who has to make the decision rather than for a specialist who audits it afterwards.
It is role-sensitive by design. Everybody completes the literacy core in modules 1 to 3, and the scenarios in module 7 differ for managers, for the people building workflows, and for compliance staff.
The method is the one every course here runs on. You record how your team handles data today, write the policy and its review step, put both in force, then measure how the decisions changed.
One boundary is stated in the course and worth stating here: this is practitioner training on governance, and it is not legal advice. Module 5 is explicit about where the material stops and your counsel starts.
Common questions
It is free. The first module of every course opens instantly, and one free account unlocks the rest of that course. Everything on this site is free to use.
A course completes when your workflow runs live and you have measured it. You record a baseline in module 1, launch the workflow into a working environment, then measure the same thing again. That pairing is what makes the completion record worth sharing.
Yes. The first module of every course plays for everyone, with a free account needed only from module 2.
Name, role, organization, and a few questions about the workflow you want to improve. It takes about a minute, and it is what lets the guided labs use your own workflow as the project.
One workflow you own, permission to change it, and the tools your team already uses. Applied AI infrastructure also assumes access to a GPU cloud account, and AI starter for small business runs on everyday business tools.
A one-page record inside the course. Before you launch, you note a baseline on time, cost, or quality. After you launch, you measure again. The sheet holds both numbers and the difference between them.
Instructor
Roan Weigert
Records all five courses
Hackathon judge and AI content creator, and host of the AI Insights San Francisco podcast. Writes this curriculum and records every core lesson.
Other courses
The other four courses
Each one takes a different kind of work through the same five steps. Pick the one closest to your job.
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Open to everyone, with no account. You finish it holding a current-state baseline.