Human-AI Collaboration: Agents, Judgment & Workflows

Coursera via Coursera Professional Certificate

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Provider

Coursera Professional Certificate
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

12 weeks, 6 hours a week
Sessions

Self-Paced
Level

Beginner

Found in

Overview

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Generative AI is changing how professionals think, decide, and deliver. This Advanced-Level Professional Certificate builds the collaboration skills that make AI-augmented work reliable, not just fast. Across four courses, you will learn to frame problems for AI, design and refine prompts, orchestrate multi-step workflows, work alongside AI agents (including autonomous ones), and apply calibrated judgment when AI outputs feed real decisions. You will produce portfolio-ready artifacts: task allocation matrices, prompt libraries, agent blueprints, red-team reports, confidence rubrics, and decision briefs. You will also practice the human side of the loop—spotting hallucinations, running root cause analysis on AI-informed decisions, and building learning loops that improve your work over time. This program is designed for early-career professionals in any function—analysts, coordinators, associates, and individual contributors—who already use, or are about to use, generative AI at work. No coding experience is required; comfort with everyday productivity tools is enough. You will use widely available chat interfaces (such as ChatGPT, Claude, Gemini, or Copilot) and no-code agent builders. The program closes with career development guidance for professionals moving into AI-augmented roles.

Syllabus

Course 1: Foundations of Human-AI Learning & Teaming
Course 2: Strategic AI Communication
Course 3: AI Agent Collaboration and Multimodal Applications
Course 4: Critical AI Decision-Making
Course 5: Launching Your AI-Augmented Career

Courses

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This course moves from mindset to build. You will learn to work with AI as a strategic partner, construct and deploy AI agents, orchestrate multi-step and multi-agent workflows, and prompt across text, image, and data modalities. You will also learn to supervise autonomous agents—deciding when to intervene and when to let them run. Hands-on work includes an AI-readiness assessment, a workforce skilling plan, a deployed agent that automates a recurring task, a multi-agent system blueprint, a multimodal workflow, and a risk-scored intervention matrix. By the end you will have a working agent, a multi-agent workflow, and the supervision protocols to run them responsibly. You will use generative AI chat interfaces, no-code and low-code agent frameworks such as CrewAI, multimodal AI tools spanning text, image, and code, prompt orchestration tools, and Coursera Coach. Basic familiarity with generative AI tools is assumed.
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This course builds the judgment layer of AI-augmented work. You will learn to evaluate AI outputs critically, red-team them for bias and hallucination, run root cause analysis on AI reasoning, calibrate your confidence, and justify AI-informed decisions to stakeholders. A short GenAI Literacy module on responsible and ethical AI use extends the content into everyday workplace practice. You will complete a reliability audit, execute a red-team protocol with a failure-mode report, run structured analysis using frameworks such as 5 Whys, fishbone, and Pareto, score outputs against a confidence rubric, and produce a stakeholder-ready decision brief. By the end you will have a defensible framework for making AI-informed decisions at work. You will work with generative AI chat interfaces, analytical frameworks and templates (provided), Miro, synthetic media verification tools, and Coursera Coach. Ideal for professionals preparing for greater decision-making responsibility.
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This course establishes the science and mindset behind effective human-AI collaboration. You will explore how complementary intelligence works, how AI agents learn and adapt, and how to teach AI your professional context so its outputs reflect your role and expertise. You will also build the personal learning loops that keep your skills sharp as AI capabilities grow. Through hands-on activities you will produce a task allocation matrix, a reliance map for your role, a context-teaching prompt library, and a continuous learning-loop playbook. By the end, you will have a clear map of when to lead, when to follow, and when to co-work with AI—plus a portfolio-ready human-AI teaming playbook built around your own responsibilities. You will work with generative AI chat interfaces such as ChatGPT and Claude, Coursera Coach, and provided task-allocation and reliance-mapping templates. No prior AI experience is required.
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This short course helps you turn everything you built across the program into your next career move. You'll learn to articulate your human-AI collaboration skills for job applications, tailor your resume and portfolio around the artifacts you produced, and present yourself convincingly for roles that involve working alongside AI. You'll position the work you can already show—teaming playbooks, prompt libraries, agent workflows, and decision-justification packages—as evidence of what you can do, not just claims on a page. You'll then practice interviews focused on the topics these roles probe most: responsible AI use, agent design, and calibrated judgment about when to trust or override AI outputs. Designed for professionals preparing to apply for roles that involve generative AI collaboration, agent-based workflows, or AI-augmented decision work. No coding required; you'll build job-search materials using tools you already use.
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This course develops the prompting fluency that underpins every other AI-augmented skill. You will learn to frame problems for AI, design prompts from basic to advanced techniques, run iterative refinement across professional domains, and orchestrate multi-step prompt workflows with built-in quality checkpoints. You will decompose complex problems into sequenced queries, configure AI parameters to control style and accuracy, inject context for sharper outputs, and connect multiple AI tools into a single automated workflow. Along the way you will build a domain-adapted prompt library and a working orchestration for a real professional task. You will practice with generative AI chat interfaces such as ChatGPT, Claude, and Gemini, prompt engineering platforms, and Coursera Coach. This course pairs well with any role that produces analysis, writing, research, or communication.