AI curriculum
Course outline for AI Risk, Compliance and Audit
Risk controls need traceable evidence and a response process. Build a sample control matrix and audit trail while distinguishing technical evidence from jurisdiction-specific compliance conclusions.
About AI Risk, Compliance and Audit
Risk controls need traceable evidence and a response process. Build a sample control matrix and audit trail while distinguishing technical evidence from jurisdiction-specific compliance conclusions.
AI Risk, Compliance and Audit Course Objectives
- Create an AI risk and control matrix.
- Specify evidence for a control review.
- Draft an incident response and follow-up record.
Pre-requisites
- Familiarity with organizational risk or operational processes.
- Basic understanding of AI systems; coding is not required.
Lab Setup
- Computer with a document editor and spreadsheet.
- Use fictional incidents and synthetic audit logs; no access to regulated production data is needed.
Detailed Course Outline
Proposed modulesModule 1: Risk and controls
- Risk management
- Control design
- Compliance
- Audit trails
Practical outcome: Link identified risks to controls and evidence requirements.
Module 2: Evidence and response
- Decision provenance
- Evidence collection
- Incident management
Practical outcome: Reconstruct a sample decision and document response actions.
Practical exercise
- Review a fictional AI incident, assemble an evidence record, and identify control gaps without asserting legal compliance.
How we train
Contact us for full course details, including duration, delivery options and lab requirements.
Ask about exercises, instructor feedback and the prior knowledge you need. Tool-specific courses marked provisional may become modules in a broader course.
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