Master AI Agent Collaboration

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Master AI Agent Collaboration

Instructor: Professionals in the Industry

Included with Learn more

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

3 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

3 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Delegation: It’s a choice, not a default. Weigh task complexity, impact, and risk to decide if AI should own it, assist, or stay out.
Verification: It’s a discipline, not a gut check. Checking sources, testing figures, and flagging risks build trust in AI workflows.
Accountability: Reviewing AI output and documenting whether to accept, refine, or escalate is the new operational standard.
Competency: Spotting AI failures like hallucinations or drift is a core skill that turns passive users into vital collaborators.

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There are 3 modules in this course

What would you do differently at work tomorrow if you actually knew when to trust your AI agent — and when to override it? This Short Course was created to help Operations Management professionals build a practical framework for working alongside AI agents with confidence and control. By completing this course, you'll be equipped to categorize your daily tasks for delegation, run structured verification checks on agent-generated outputs, and make documented, defensible decisions — starting the very next workday. By the end of this course, you will be able to:

- Analyze current workflow tasks to categorize each as delegate-to-agent, shared, or retain-manual based on complexity and risk - Create a verification checklist that specifies data-source checks, factual spot-tests, and privacy red-flags for agent outputs - Evaluate an agent-generated output against the checklist and document whether to accept, refine, or escalate the result This course is unique because it is designed specifically for non-technical operations workers handed a new AI tool with no playbook — addressing hallucination, drift, and runaway loops in plain language.The course introduces common AI agent failure modes including hallucinations, stale context, incorrect tool usage, privacy exposure, workflow breakdowns, drift, and runaway loops.

Learners apply a structured framework to analyze their own workflow tasks and categorize each as delegate-to-agent, shared, or retain-manual based on complexity and risk.

What's included

1 video1 reading2 assignments

Learners construct a personal one-page verification checklist specifying data-source checks, factual spot-tests, and privacy red-flags for reviewing AI agent outputs.

What's included

2 videos1 reading2 assignments

2 videosTotal 7 minutes

The Report That Almost Went Out: A Verification Story2 minutes
Building a Verification Checklist in Microsoft Copilot Workflows4 minutes

1 readingTotal 10 minutes

Verification Checklist Reference: Components, Criteria, and Examples10 minutes

2 assignmentsTotal 18 minutes

Draft Your One-Page Verification Checklist13 minutes
Knowledge Check: Build Your Verification Checklist5 minutes

Learners evaluate a Copilot-generated output against their verification checklist, make a documented accept, refine, or escalate decision, and complete their personal Agent Collaboration Playbook.

What's included

1 video2 readings3 assignments

1 videoTotal 6 minutes

Accept, Refine, or Escalate: The Decision Framework Explained6 minutes

2 readingsTotal 18 minutes

Documenting Your Decision: Standards, Language, and Formats10 minutes
Working Through a Decision: A Step-by-Step Evaluation Walkthrough8 minutes

3 assignmentsTotal 40 minutes

Complete Your Playbook: Document an Evaluation Decision15 minutes
Knowledge Check: Evaluate, Decide, and Document5 minutes
Master AI Agent Collaboration — Graded Assessment20 minutes

Instructor

Professionals in the Industry

457 Courses84,346 learners

Offered by

Coursera

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