Udemy

NIST AI RMF: AI Governance & Risk Management Training

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  • 65 Students
  • Updated 3/2026
4.4
(09 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
3 Hour(s) 11 Minute(s)
Language
English
Taught by
Varinder K
Rating
4.4
(09 Ratings)

Course Overview

NIST AI RMF: AI Governance & Risk Management Training

NIST AI RMF: GOVERN, MAP, MEASURE & MANAGE : AI Risk & Governance Training

Foundations of AI Risk Management

  • What a Risk Management Framework is and why AI systems need one

  • Introduction to NIST's AI RMF — its purpose, structure, and key principles

  • NIST's broader efforts toward building safe, secure, and trustworthy AI

  • Types of risks and harms that arise from AI system deployment

AI RMF Core Concepts

  • Understanding risk tolerance in the context of AI systems

  • Key risk management challenges unique to AI — bias, opacity, drift, and scale

  • How to prioritize AI risks effectively across an organization

  • How the NIST AI RMF enables effective, structured risk management

GOVERN Function (6 Sub-categories)

  • What the GOVERN function covers and why it comes first

  • GOVERN 1 through GOVERN 6 — policies, accountability, culture, and oversight

  • Case Study: Implementing GOVERN in a real AI-driven recruitment system

  • How Governance connects to and enables MAP, MEASURE, and MANAGE

MAP Function (5 Sub-categories)

  • What the MAP function does — categorizing AI risks in context

  • MAP 1 through MAP 5 — identifying AI system context, impacts, and risk categories

  • How to map risks to specific AI use cases in your organization

MEASURE Function (4 Sub-categories)

  • What the MEASURE function covers — quantifying and analyzing AI risks

  • MEASURE 1 through MEASURE 4 — metrics, evaluation, and AI system testing

  • How to assess trustworthiness characteristics: fairness, explainability, robustness

MANAGE Function (4 Sub-categories)

  • What the MANAGE function covers — responding to and treating AI risks

  • MANAGE 1 through MANAGE 4 — risk response, residual risk, and incident handling

  • How to build ongoing risk management into your AI development lifecycle

Real-World Application

  • AI in hiring processes — risks, governance failures, and framework application

  • Key concepts synthesis — connecting all 4 functions into a complete picture

  • Best practices for organizations at any stage of AI adoption

Course Structure at a Glance

Section 1 — Risk Management Basics & NIST AI RMF Introduction

Section 2 — Foundational AI Risk Concepts: Tolerance, Prioritization & Challenges

Section 3 — GOVERN Function: All 6 sub-categories + Recruitment Case Study

Section 4 — MAP Function: All 5 sub-categories

Section 5 — MEASURE Function: All 4 sub-categories

Section 6 — MANAGE Function: All 4 sub-categories

Section 7 — Real-World Examples, Knowledge Check Quiz & Conclusion

Why This Matters Right Now

  • The EU AI Act is now in force wherein organizations need AI governance frameworks immediately

  • NIST AI RMF is the most widely referenced AI risk standard in the US and globally

  • Companies deploying AI in hiring, lending, healthcare, and public services face growing regulatory scrutiny

  • Demand for professionals with AI governance and risk management skills is growing faster than supply

  • The NIST AI RMF directly informs ISO 42001 the new AI management system standard

Course Content

  • 7 section(s)
  • 38 lecture(s)
  • Section 1 Lets cover some basics first
  • Section 2 AI RMF - Part 1 Foundational Information
  • Section 3 Core of AI Framework
  • Section 4 MAP Function
  • Section 5 Measure Function
  • Section 6 Manage Function
  • Section 7 Final Section

What You’ll Learn

  • Explain what a Risk Management Framework is and why AI systems require a dedicated framework separate from traditional IT risk approaches, Describe the purpose, structure, and key principles of the NIST AI Risk Management Framework (AI RMF) and how it supports trustworthy AI development, Identify the types of risks and harms that can arise from AI system deployment including bias, opacity, fairness failures, and unintended consequences, Understand risk tolerance in the context of AI systems and how organizations set acceptable risk thresholds for AI use cases, Apply risk prioritization techniques to determine which AI risks require immediate attention versus ongoing monitoring, Explain the relationship between all 4 core functions : GOVERN, MAP, MEASURE, and MANAGE - and how they work together as an integrated framework, Walk through all 6 sub-categories of the GOVERN function — covering AI governance policies, organizational accountability, culture, and oversight structures, Apply the MAP function across all 5 sub-categories to categorize AI system context, identify stakeholder impacts, and define risk categories for specific use ca, Use the MEASURE function across all 4 sub-categories to evaluate AI system trustworthiness characteristics — including fairness, explainability, robustness, and, Implement the MANAGE function across all 4 sub-categories to respond to identified AI risks, handle residual risk, and build incident response into AI operation, Analyze a real-world case study of the GOVERN function applied to AI driven recruitment system identifying governance failures and correct framework application, Examine AI use in hiring processes as a high-risk AI deployment scenario and understand what risk controls and governance structures are required, Understand NIST's broader efforts toward safe, secure, and trustworthy AI and how AI RMF connects to emerging regulations including the EU AI Act & ISO 42001, Recognize the unique risk management challenges posed by AI systems including model drift, algorithmic bias, lack of explainability, Synthesize all framework functions into a complete organizational AI risk management approach applicable to AI development, procurement, and deployment decision


Reviews

  • S
    Steven Shawcross
    4.0

    Good course gave me the basics of NIST AI RMF, But I personal need a deeper dive but it was a good start.

  • N
    Narayana Moorthy
    4.5

    Excellent Course. Thanks

  • S
    Sujitha
    5.0

    This lecture on NIST AI Risk management is a must watch for anyone interested in the future of AI. This video breaks down complex topics in a clear & engaging way, making it accessible for both beginners & experts. It provides valuable insight into managing AI risk, ensuring ethical AI deployment, and aligning AI system with security & compliance standards. Thanks to the lecture who explains all topics very clear, waiting for more videos related to AI.

  • R
    Rakesh
    5.0

    This video on NIST AI Risk Management is incredibly insightful! It breaks down complex concepts into easy-to-understand steps, making AI risk management accessible for everyone, regardless of their technical background. I especially appreciate how the video highlights key components. It's a must-watch for anyone looking to responsibly implement AI while staying ahead of potential risks. Great content. Appreciate the effort of tutor.

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