This course introduces learners to designing intelligent agents using Microsoft Copilot Studio, a powerful low-code platform. You'll move from mastering Copilot basics to building and deploying AI-powered agents that solve real business problems. Through hands-on labs and guided projects, you’ll practice prompt design, logic workflows, platform integrations, and performance tuning. By the end, you’ll have the confidence to build, iterate, and launch your own business-ready AI solutions.

Profitez d'une croissance illimitée avec un an de Coursera Plus pour 199 $ (régulièrement 399 $). Économisez maintenant.

Expérience recommandée
Compétences que vous acquerrez
- Catégorie : AI Workflows
- Catégorie : Business Logic
- Catégorie : Application Deployment
- Catégorie : Prompt Engineering
- Catégorie : Performance Tuning
- Catégorie : Generative AI Agents
- Catégorie : Model Deployment
- Catégorie : No-Code Development
- Catégorie : User Feedback
- Catégorie : AI Enablement
- Catégorie : Scalability
- Catégorie : Data Integration
- Catégorie : Microsoft Copilot
Détails à connaître

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Il y a 3 modules dans ce cours
In this lesson, learners will dive deep into the architecture and core capabilities of Microsoft Copilot Studio. You’ll examine what makes Copilot Studio different from traditional bot frameworks—its low-code interface, AI integration, and flexible data connectors. By comparing components like topics, entities, trigger phrases, and generative answers, you’ll build a mental model for how agents function from start to finish.
Inclus
3 vidéos2 lectures1 devoir
This lesson walks learners through the full cycle of building an AI-powered agent in Copilot Studio—from setting up topics to layering in generative responses and adding external data. You’ll apply structured logic and explore how to make your agent more human-like and adaptive using Copilot’s GPT-powered features.
Inclus
2 vidéos1 lecture1 devoir
You’ve built your agent—now what? In this final lesson, learners will test their agents, explore channel deployment (Teams, websites, etc.), and gather user feedback to refine behavior. You’ll also explore how to monitor, evaluate, and continuously improve agents post-deployment for real-world scale.
Inclus
3 vidéos1 lecture3 devoirs
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