Udemy - Agent2Agent Protocol (A2A) - AI Governance and Compliance torrent

Agent2Agent Protocol (A2A): AI Governance & Compliance
https://WebToolTip.com
Published 7/2026

Created by Data Universe

MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch

Level: All Levels | Genre: eLearning | Language: English | Duration: 33 Lectures ( 2h 46m ) | Size: 1.5 GB
A2A vs MCP, agent identity, auditability, EU AI Act, ISO 42001 & NIST AI RMF. Multi-agent governance without coding
What you'll learn

⚡ Understand what the A2A protocol is, why it exists, and how it enables AI agents to discover and collaborate with each other.

⚡ Explain how A2A works without jargon: agent cards, tasks, messages, artifacts, interaction modes, and the opacity principle.

⚡ Distinguish clearly between A2A and MCP, understanding when to use each protocol and how they complement each other.

⚡ Identify the new governance risks that emerge when agents collaborate autonomously and delegate tasks to other agents.

⚡ Apply security controls for multi-agent systems: agent identity, authentication, data in transit, and access boundaries.

⚡ Design traceability and auditability mechanisms that reconstruct what agents did and why in multi-agent workflows.

⚡ Navigate the regulatory implications of A2A under the EU AI Act, ISO 42001, and the NIST AI Risk Management Framework.

⚡ Map accountability chains in multi-agent flows and define who is responsible when cascading errors cross agent boundaries.

⚡ Evaluate vendor A2A claims critically, write interoperable-agent usage policies, and present A2A risks to leadership.

⚡ Apply a maturity checklist to assess your organization's readiness for A2A adoption and avoid the five most common mistakes.
Requirements

❗ No programming or engineering background required — this course is designed for governance, compliance, and business professionals.

❗ Basic familiarity with AI concepts like agents or LLMs is helpful but not required — all foundational concepts are introduced clearly.

❗ All you need is a role involving AI governance, risk, compliance, or strategic oversight and a desire to lead responsibly.