Microsoft Intelligent Applications Builder Associate (AB-410) Cert Prep

Course details

The Microsoft Intelligent Applications Builder Associate (AB-410) exam tests your ability to build intelligent apps that combine Power Platform tools with Azure AI—apps that use copilots, agents, and automation alongside traditional forms and workflows.

Designed for Power Platform makers and developers adding AI to their work, this course prepares you for the exam and the job. Get familiar with Power Apps, Power Automate, Power Pages, Copilot Studio, and Dataverse, plus governance and application lifecycle management. Then, explore Azure AI services, the Microsoft Foundry platform, prompt engineering, retrieval-augmented generation (RAG), agent design, and responsible AI. By the end, you will know which tool fits which problem, how to ground models in your own data, and how to balance trade-offs like cost, latency, and performance.

Concepts

Introduction

Introduction to the Microsoft Intelligent Applications Builder Associate (AB-410) exam
The evolution of Microsoft Azure
Definition of cloud computing
Azure in today's cloud ecosystem
Why Azure is a strategic platform for administrators
What is Microsoft Power Platform
What is an intelligent application
Core cloud service models
Azure's shared responsibility model
Azure resource management
Resource groups explained
Resource lifecycle and dependencies

AI Foundations for Intelligent App Builders

Course introduction
AI and modern AI applications
Overview of Azure AI services
Types of AI solutions
Service selection strategies
Introduction - Plan and design AI solutions on Azure
Introduction to AI Hub
What are AI models in AI Hub
Responsible AI principles
Summary

Generative AI and Model Design

Core generative app flow - Input, prompt construction, model invocation, and response handling
Chat vs. completion-style inference
Model selection
Streaming vs. non-streaming responses
Session and state handling in application design
What is an AI prompt
Introduction to prompt templates
Summary

AI Agents and Copilot Studio

Introduction - Understand AI agents and tool-enabled systems
What is an AI agent
What is an agent in Power Platform
Agents vs. traditional applications
When to use agents vs. standard AI apps
Memory in AI agents
Planning vs. single-step prompting
Tool use and function calling
Introduction to Microsoft Copilot in Power Platform
What is Microsoft Copilot Studio

Prompt Engineering, RAG, and AI Optimization

Introduction - Optimize AI applications and grounding strategies
Prompt engineering fundamentals
Grounding with retrieval-augmented generation (RAG)
Fine-tuning concepts (when to use)
Comparing prompting, RAG, and fine-tuning
Performance trade-offs (cost, latency, accuracy)
Documents in RAG workflows
Summary

Responsible AI and Safety Controls

Introduction - Implement responsible AI and safety controls
Responsible AI lifecycle (map, measure, mitigate)
Introduction to responsible AI in Power Platform
Safety risks in AI applications
Harm categories and severity levels
Trade-offs between safety and usability
System messages and guardrails
Prompt attacks and jailbreaks
Moderating input and output
Summary

Azure Language and Document Intelligence

Introduction
NLP vs. generative AI (when to use each)
Deterministic vs. probabilistic outputs
Azure AI Language capabilities (NER, sentiment, classification)
Language detection and PII detection
Document Intelligence overview
Prebuilt vs. custom document models
Extracting structured data (text, tables, fields)
Summary

Azure Vision and Speech

Introduction - Plan and design AI solutions on Azure
Vision
Speech
Summary

Microsoft Foundry Platform

Microsoft Foundry
Microsoft Foundry Tools
Microsoft Foundry Local
Microsoft Foundry Control Plane
Microsoft Foundry IQ
Microsoft Foundry Agent Service
Microsoft Agent Framework

Power Platform Core Concepts

What is a Power Platform environment
What is a solution in Power Platform
What is Dataverse
Introduction to Dataverse tables
Introduction to application lifecycle management
What are table relationships
What are prompt columns
What are row summaries
Introduction to the Dataverse security model
What are calculated, rollup, and formula columns
What are business rules
What is a business process flow

Power Apps - Model-Driven and Canvas Apps

What is a model-driven app
What is a canvas app
What are generative pages
Introduction to forms and views
Dashboards and charts in model-driven apps
Introduction to Power Fx
What are variables and collections
What are named formulas and user-defined functions
Introduction to component libraries
What is error handling in canvas apps
Introduction to app accessibility and responsiveness
What is Power Apps Monitor
Introduction to Power Pages

Power Automate and Business Automation

What is Power Automate
What is a cloud flow
Introduction to flow triggers
What are connectors
What are approvals in Power Automate
Introduction to conditions and loops
End of the Microsoft Intelligent Applications Builder Associate (AB-410) course