Microsoft AI

Copilot Studio + Power Automate

4 - 6 Hours 4 Modules

Overview

Main Theme: Microsoft AI / Copilot

Workload: 4 - 6 Hours

Level: Advanced

Target Audience: Solution Architects, Low-Code Developers, and Process Analysts

ABOUT THE TRAINING

This training focuses on creating an "Invisible Interface," where the technical complexity of the systems is hidden behind a natural conversation. By combining the "brain" (Copilot Studio) with the "muscles" (Power Automate), we empower the team to build agents that not only answer questions but also perform real tasks in legacy systems, databases, and SaaS applications, ensuring that the user only needs to know how to ask for the task to be completed.

Objective

Empower professionals to orchestrate automated workflows through chat, using complex variable extraction and API integrations to solve high-criticality business problems with full traceability.

TRAINING MODULES

Intent Mapping

Advanced techniques to make the Copilot extract precise variables from loose phrases. The student will learn to configure the agent to identify and isolate data such as "Supplier ID", "Value", and "Date" from a paragraph of text, preparing them for automatic processing.

Custom Connectors and API Integration

Use of HTTP calls and connectors to link the chat to systems that do not have native integration. The focus is to enable the agent to interact with proprietary or legacy systems, expanding the automation frontier beyond the Microsoft ecosystem.

Conditional Logic and Resilience (Error Handling)

Development of robust flows that do not "freeze." Learning how to program the bot to identify failures in Power Automate (e.g., error when writing to a database) and inform the user in a technical and helpful manner, suggesting alternative resolution paths.

Practical Lab: Automation of Requests and Notifications

Hands-on exercise: the student will create an agent that receives a user request and automatically triggers a flow in Power Automate. The focus is to master the data transfer from chat to the actual workflow.

Materiais complementares