Certified: The IAPP AIGP Audio Course

By Jason Edwards

Listen to a podcast, please open Podcast Republic app. Available on Google Play Store and Apple App Store.

Image by Jason Edwards

Category: Technology

Open in Apple Podcasts


Open RSS feed


Open Website


Rate for this podcast

Subscribers: 0
Reviews: 0
Episodes: 59

Description

Certified: The IAPP AIGP Audio Course is built for professionals who need a practical path into AI governance without having to stop their day job to get there. It is a strong fit for privacy professionals, compliance teams, risk managers, security leaders, legal and policy staff, product managers, consultants, and anyone else who now has AI oversight in their role. The course assumes you are motivated and capable, but not necessarily deep in technical machine learning work. It starts from clear foundations and then moves into the governance, risk, accountability, and decision-making issues that matter in real organizations. If you are trying to understand how responsible AI programs are structured, how governance connects to business use, and how to prepare for the AIGP certification in a way that feels manageable, this course gives you a steady and usable learning path. You will learn the language, concepts, and operating mindset behind modern AI governance in a format designed for listening first. The lessons explain how organizations think about AI risk, accountability, transparency, oversight, policy design, lifecycle controls, third-party considerations, documentation, and cross-functional decision-making. Instead of sounding like a policy manual read into a microphone, the teaching is built to be clear in your headphones, in your car, on a walk, or between meetings. Each episode is shaped to help you absorb complex ideas through straightforward explanation, practical framing, and repeated connection to real workplace decisions. That matters because AI governance can feel abstract when it is presented as a wall of terms. In audio form, the material becomes easier to follow, easier to revisit, and easier to connect to the kinds of judgment calls professionals face every day. What sets this course apart is that it treats the certification as important, but not as the only goal. You are not just memorizing terms for a test. You are building a working understanding of how AI governance fits into real organizations, how roles and responsibilities should be defined, where risk and compliance pressures show up, and how to think clearly when rules, innovation, and business pressure collide. The teaching stays grounded, avoids unnecessary jargon, and respects the fact that most learners want both exam readiness and practical value. Success here means more than finishing episodes. It means you can hear a new AI initiative, understand the governance questions behind it, speak more confidently across teams, and walk into the IAPP AIGP exam with a stronger sense of structure, purpose, and control.

Episode Date
Welcome to the AIGP Course!
Apr 19, 2026
Episode 58 — Synthesize Development and Deployment Governance into One Defensible Decision-Making Framework
Apr 04, 2026
Episode 57 — Establish External Communication Plans and Deactivation or Localization Controls for AI
Apr 04, 2026
Episode 56 — Document Incidents and Post-Market Monitoring While Reducing Secondary Uses and Downstream Harms
Apr 04, 2026
Episode 55 — Verify Deployed AI with Audits, Red Teaming, Threat Modeling, and Security Testing
Apr 04, 2026
Episode 54 — Conduct Ongoing Monitoring, Maintenance, Updates, and Retraining After Deployment
Apr 04, 2026
Episode 53 — Apply Governance Controls to Deployment Through Data, Risk, Issue, and User Training
Apr 04, 2026
Episode 52 — Understand the Unique Risks, Opportunities, and Obligations of Deploying Proprietary AI
Apr 04, 2026
Episode 51 — Evaluate Vendor Contracts and Licensing Terms Before You Deploy AI
Apr 04, 2026
Episode 50 — Assess Selected AI Systems with Focused Impact Reviews Before Deployment
Apr 04, 2026
Episode 49 — Choose Deployment Options Across Cloud, On-Premise, Edge, Fine-Tuning, RAG, and Agentic Architectures
Apr 04, 2026
Episode 48 — Compare AI Model Types Before Choosing What Your Organization Will Deploy
Apr 04, 2026
Episode 47 — Evaluate Deployment Context, Business Goals, Ethics, Data, and Workforce Readiness
Apr 04, 2026
Episode 46 — Review AI Development Governance from Impact Assessments to Public Disclosures
Apr 04, 2026
Episode 45 — Meet Transparency Duties with Technical Documentation, Instructions, and Monitoring Plans
Apr 04, 2026
Episode 44 — Investigate AI Incidents with Cross-Functional Teams Tracing Drift, Data Gaps, and Brittleness
Apr 04, 2026
Episode 43 — Assess Production AI After Release with Audits, Red Teaming, Threat Modeling, and Security Testing
Apr 04, 2026
Episode 42 — Build Continuous Monitoring, Maintenance, Updates, and Retraining Rhythms for Released AI
Apr 04, 2026
Episode 41 — Assess Release Readiness with Model Cards and Conformity Requirements
Apr 04, 2026
Episode 40 — Manage Training and Testing Issues While Documenting Results for Compliance
Apr 04, 2026
Episode 39 — Improve Interpretability and Reduce Model Risk During AI Testing
Apr 04, 2026
Episode 38 — Plan Training and Testing Across Unit, Integration, Validation, Performance, Security, and Bias
Apr 04, 2026
Episode 37 — Establish Data Lineage and Provenance You Can Defend Under Scrutiny
Apr 04, 2026
Episode 36 — Govern Training Data Rights, Quality, Quantity, Integrity, and Fitness for Purpose
Apr 04, 2026
Episode 35 — Document Design and Build Decisions to Prove Compliance and Manage Risk
Apr 04, 2026
Episode 34 — Strengthen AI Designs Through Use-Case Evaluation, Benchmarking, Pilots, and Testing
Apr 04, 2026
Episode 33 — Identify and Mitigate Design Risks with Harms Matrices, Risk Hierarchies, and Stakeholder Mapping
Apr 04, 2026
Episode 32 — Build Human Oversight, Metrics, Thresholds, Feedback, and Controls into Design
Apr 04, 2026
Episode 31 — Design AI Systems with Clear Purpose, Requirements, Architecture, and Model Choice
Apr 04, 2026
Episode 30 — Perform Impact Assessments Early to Shape Safer AI Design Decisions
Apr 04, 2026
Episode 29 — Define Business Context and Use Cases Before Building Any AI System
Apr 04, 2026
Episode 28 — Review the Governance Foundations and Legal Duties Most Likely to Matter
Apr 04, 2026
Episode 27 — Understand ISO 22989, ISO 42001, and ISO 42005 in AI Governance
Apr 04, 2026
Episode 26 — Use the NIST AI RMF and Playbook to Structure Governance
Apr 04, 2026
Episode 25 — Apply OECD Trustworthy AI Principles, Frameworks, Policies, and Recommended Practices
Apr 04, 2026
Episode 24 — Compare Enforcement, Penalties, and Duties for Providers, Deployers, Importers, and Distributors
Apr 04, 2026
Episode 23 — Understand the Distinct Requirements That Apply to General-Purpose AI Models
Apr 04, 2026
Episode 22 — Govern Human Oversight, Transparency, Notification, and Quality Management Requirements
Apr 04, 2026
Episode 21 — Operationalize AI Law Requirements for Risk Management, Documentation, and Record Keeping
Apr 04, 2026
Episode 20 — Map AI Risk Classifications from Prohibited Uses to Minimal Risk
Apr 04, 2026
Episode 19 — Interpret Consumer Protection and Product Liability Risks in AI Systems
Apr 04, 2026
Episode 18 — Apply Nondiscrimination Law to AI in Employment, Credit, Housing, and Insurance
Apr 04, 2026
Episode 17 — Understand How Intellectual Property Law Shapes AI Training and Use
Apr 04, 2026
Episode 16 — Protect Sensitive and Special Category Data When AI Uses Biometrics
Apr 04, 2026
Episode 15 — Master Controller Obligations for AI Impact Assessments, Rights, Transfers, and Records
Apr 04, 2026
Episode 14 — Embed Data Minimization and Privacy by Design into AI Systems
Apr 04, 2026
Episode 13 — Navigate Transparency, Choice, Lawful Basis, and Purpose Limits in AI
Apr 04, 2026
Episode 12 — Manage Third-Party AI Risk Through Assessments, Contracts, Procurement, and Acceptable Use
Apr 04, 2026
Episode 11 — Update Privacy, Security, Data Governance, and IP Policies for AI
Apr 04, 2026
Episode 10 — Establish Life Cycle Policies That Drive Oversight and Accountability End to End
Apr 04, 2026
Episode 9 — Differentiate Developers, Providers, Deployers, and Users in the AI Governance Model
Apr 04, 2026
Episode 8 — Tailor AI Governance to Company Size, Maturity, Industry, and Risk Tolerance
Apr 04, 2026
Episode 7 — Create AI Terminology, Strategy, and Governance Training for Every Stakeholder
Apr 04, 2026
Episode 6 — Build Cross-Functional AI Governance Collaboration That Actually Works Across the Organization
Apr 04, 2026
Episode 5 — Define AI Governance Roles and Clarify Who Owns Which Decisions
Apr 04, 2026
Episode 4 — Apply Responsible AI Principles Across Fairness, Safety, Privacy, Transparency, and Accountability
Apr 04, 2026
Episode 3 — Understand AI Risks, Harms, and Why Governance Cannot Be Optional
Apr 04, 2026
Episode 2 — Grasp AI Definitions, Types, and Core Use Cases That Matter
Apr 04, 2026
Episode 1 — Decode the AIGP Exam Blueprint, Question Styles, Policies, and Spoken Study Plan
Apr 04, 2026