Developing Technical Audits for AI
AI law and regulation is changing fast. Learn global AI governance, fairness, and bias principles in this course. Stay compliant and ethical with AI.
Course Content
Developing Technical Audits for AI is an intermediate-level Pluralsight course taught by Darryl Brown. It runs 18m, is taught in English, and includes a certificate of completion. It is a paid course, first published September 2025.
Navigate the rapidly evolving world of AI with confidence. Engineers and regulatory bodies are facing an unprecedented surge in data management, data processing, and data generation capabilities. Becoming a responsible AI champion is more critical than ever.
This course, Developing Technical Audits for AI, equips you with the skills to audit for responsible AI principles. You'll learn practical evaluation and detection techniques to assess fairness, transparency, accountability, safety, and privacy throughout the entire AI lifecycle.
Here's what you'll cover:
- Understanding the Regulatory Landscape: Gain familiarity with the laws and policies governing AI audits and assessments.
- Practical Application with Case Studies: Apply auditing techniques through a hands-on case study.
- Utilizing Auditing Frameworks: Discover and leverage powerful AI auditing frameworks like Fairlearn.
- NIST AI Risk Management Framework (RMF): Learn how to apply the NIST RMF to effectively manage and monitor AI risks.
By the end of this course, you'll possess the skills of an AI audit engineer, ready to proactively manage and mitigate risks in your AI deployments. Master the techniques to ensure your AI systems are not only powerful but also ethically sound and compliant.
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