MS-AI103.KZ1

Azure AI Engineering: Build, Deploy, and Manage Enterprise AI Solutions

Master enterprise AI development with our comprehensive Azure AI Engineering certification training course, featuring 102 hands-on practice exercises.

26 Interactive Lessons and 258 topics mapped to the official exam objectives
192 Practice Test Questions

Intermediate Self-paced · 1 year access

26Interactive Lessons

258Topics

192Practice Test Questions

10Flashcards

10Glossary of terms

01 / Skills you'll get

What you will be able to do

Try Free → No credit card required

This Azure AI Engineering certification training course provides a rigorous, hands-on path to mastering enterprise-grade AI solutions. You will navigate 26 comprehensive chapters covering everything from foundational machine learning to advanced RAG systems and Microsoft Foundry agent development. Unlike theoretical courses, we focus on real-world deployment, monitoring, and governance. You will tackle 160 practice quizzes and 102 exercises designed to mirror actual production challenges. Be warned: this curriculum demands technical discipline. You will face trade-offs between model latency and accuracy, and learn to manage complex AI lifecycles. If you are serious about building scalable, secure, and responsible AI agents, this is your definitive technical blueprint.

Generative AI Architecture: Mastery of transformer models, LLMs, and advanced prompt engineering patterns for reliable enterprise-grade output generation.
Retrieval-Augmented Generation: Expert implementation of vector search, document indexing, and grounding techniques to reduce model hallucinations in production.
AI Lifecycle Management: Proficiency in CI/CD for AI, monitoring model drift, and maintaining observability in complex, event-driven AI workflows.
Enterprise Governance: Ability to implement robust security, identity management, and responsible AI frameworks to ensure compliance and data privacy.

Course Highlights

26 Structured Lessons Comprehensive coverage of core course objectives
192 Practice Questions Assessment tests with detailed answer rationales
1 Year Full Access Self-paced learning accessible anytime on all devices

02 / Lessons & labs

See exactly what you will learn and practice

Download outline (PDF)

Lessons

26 Interactive Lessons · 258 topics

01 Preface 3 topics

About Microsoft
About the AI-103 Certification
How This Course Is Organized

02 Foundations of Artificial Intelligence and Azure AI 8 topics

Introduction to Artificial Intelligence
AI Disciplines and Technologies
Azure AI Platform
Enterprise AI Solutions
Responsible AI
Azure AI Development Environment
Building Your First Azure AI Application
Summary

03 Machine Learning Fundamentals 8 topics

Understanding Machine Learning
Machine Learning Problem Types
Data for Machine Learning
The Machine Learning Lifecycle
Evaluating Machine Learning Models
Common Machine Learning Challenges
Machine Learning in Azure
Summary

04 Foundation Models and Generative AI 10 topics

Emergence of Foundation Models
Neural Networks and Deep Learning Fundamentals
Understanding Transformer Models
Large Language Models (LLMs)
Embeddings and Semantic Understanding
Generative AI Capabilities
Model Adaptation Techniques
Working with Foundation Models in Azure
Responsible Generative AI
Summary

05 Planning and Managing Azure AI Solutions 5 topics

Understanding the Azure AI Engineer's Role and Responsibilities
Designing Azure Infrastructure for AI Solutions
Selecting Appropriate AI Models and Services
Deployment, Management, and Responsible AI Practices
Summary

06 Developing AI Applications with Azure OpenAI Service 10 topics

Azure OpenAI Development Environment
Azure OpenAI Service Architecture
Authentication and Secure Connectivity
Building Applications Using the Azure OpenAI SDK
Developing REST API Applications
Prompt Engineering for Applications
Managing Conversations
Building Secure Enterprise Applications
Building End-to-End Azure OpenAI Solutions
Summary

07 Prompt Engineering and AI Interaction Design 10 topics

Introduction to Prompt Engineering
Prompt Structure
Prompt Design Patterns
Designing Reliable AI Outputs
Context Management
Prompt Optimization
Prompt Security
Prompt Engineering in Azure OpenAI
End-to-End Prompt Engineering Projects
Summary

08 Retrieval-Augmented Generation (RAG) with Azure AI Search 10 topics

Understanding Retrieval-Augmented Generation
Azure AI Search Fundamentals
Document Ingestion and Indexing
Embeddings and Vector Search
Search Strategies
Building RAG Applications
Evaluating and Optimizing RAG Systems
Enterprise Security and Governance
End-to-End Enterprise RAG Solutions
Summary

09 Developing AI Agents with Microsoft Foundry 9 topics

Introduction to AI Agents
Microsoft Foundry Agent Service
Agent Planning and Reasoning
Agent Memory and Knowledge
Multi-Agent Systems
Securing and Governing AI Agents
Evaluating and Optimizing AI Agents
End-to-End Enterprise Agent Solutions
Summary

10 Implementing Computer Vision Solutions with Azure AI Vision 10 topics

Introduction to Computer Vision
Azure AI Vision Resources
Image Analysis
Optical Character Recognition (OCR)
Image Embeddings and Visual Search
Multimodal AI Applications
Building Enterprise Vision Applications
Security, Responsible AI, and Optimization
End-to-End Computer Vision Solutions
Summary

11 Implementing Natural Language Processing Solutions with Azure AI Language 10 topics

Introduction to Natural Language Processing0
Azure AI Language Resources
Text Analytics
Information Extraction
Document Understanding
Conversational Language Understanding
Building Enterprise NLP Applications
Security, Responsible AI, and Optimization
End-to-End Enterprise NLP Solutions
Summary

12 Implementing Speech AI Solutions with Azure AI Speech 10 topics

Introduction to Speech AI
Azure AI Speech Resources
Speech-to-Text Solutions
Text-to-Speech Solutions
Speech Translation
Speaker Recognition
Building Enterprise Speech Applications
Security, Responsible AI, and Optimization
End-to-End Enterprise Speech Solutions
Summary

13 Implementing Document Intelligence Solutions with Azure AI Document Intelligence 11 topics

Introduction to Document Intelligence
Azure AI Document Intelligence Resources
Document Layout Analysis
Prebuilt Document Models
Custom Document Models
Intelligent Document Processing Workflows
Integrating Document Intelligence with Azure AI
Azure Content Understanding
Security, Responsible AI, and Optimization
End-to-End Enterprise Document Solutions
Summary

14 Building Multimodal AI Applications with Microsoft Foundry 10 topics

Introduction to Multimodal AI
Processing Images and Text
Processing Documents and Text
Speech-Enabled Multimodal Applications
Building Multimodal AI Agents with Microsoft Foundry
Enterprise Integration and Deployment
Evaluating and Optimizing Multimodal Applications
Security and Responsible AI for Multimodal Solutions
End-to-End Enterprise Multimodal Solutions
Summary

15 Building and Operating AI Solutions with Microsoft Foundry 9 topics

Introduction to Microsoft Foundry Development
Building AI Workflows
Evaluation and Quality Assurance
Tracing and Debugging
Collaboration and Lifecycle Management
Deployment and Production Operations
Responsible AI, Security, and Governance
End-to-End Enterprise AI Engineering
Summary

16 Monitoring and Operating Azure AI Solutions 7 topics

Enterprise AI Operations
Monitoring and Observability
Reliability and Performance
Troubleshooting AI Applications
Operational Automation
End-to-End Enterprise AI Operations
Summary

17 Deploying and Integrating Azure AI Solutions 10 topics

AI Deployment Fundamentals
Deploying Azure AI Applications
API Management and Enterprise Integration
Serverless and Event-Driven AI
Enterprise Workflow Integration
CI/CD and Release Management
Scaling and High Availability
Monitoring and Operational Excellence
End-to-End Enterprise Deployment
Summary

18 Responsible AI, Governance, Risk, and Compliance for Azure AI Solutions 10 topics

Foundations of Responsible AI
AI Safety and Content Protection
Privacy and Data Protection
AI Governance
AI Evaluation and Risk Assessment
Compliance and Regulatory Requirements
Monitoring Responsible AI
Enterprise Responsible AI Operations
End-to-End Responsible AI Platform
Summary

19 Enterprise AI Reference Architectures and Solution Patterns 10 topics

Enterprise AI Architecture Fundamentals
Core Azure AI Architecture Patterns
Multimodal AI Architectures
Enterprise Integration Patterns
Scalability and Reliability Patterns
Security Architecture
Cost and Operational Architecture
Architecture Review and Decision Making
End-to-End Enterprise AI Reference Architectures
Summary

20 Security, Identity, Networking, and Keyless Access 10 topics

Security Fundamentals for Enterprise AI
Identity and Authentication
Authorization and Access Control
Secrets and Credential Management
Network Security
Securing Models, Agents, and AI Services
API and Application Security
Security Operations
Enterprise Security Capstone
Summary

21 Monitoring, Drift, Grounding Quality, and Search Health 10 topics

Observability Fundamentals
Monitoring Models and Agents
Model Drift and Continuous Evaluation
Grounding Quality and Retrieval Monitoring
Search Index and Ingestion Health
Tracing and Diagnostics
Dashboards, Alerts, and Automation
Performance Optimization
Enterprise Monitoring Capstone
Summary

22 Governance, Control, and Auditability of AI Agents 10 topics

Agent Governance
Tool-Access and Permission Controls
Approval Workflows and Human Oversight
Agent Memory and Data Governance
Agent Traceability and Provenance
Guardrails and Policy Enforcement
Agent Lifecycle and Change Governance
Incident Response and Remediation
Enterprise Agent Governance and Auditability Capstone
Summary

23 Microsoft Foundry Deployment, CI/CD, and Lifecycle Automation 16 topics

AI Solution Lifecycle Fundamentals
Deployment Options for Microsoft Foundry Solutions
Environment Strategy
Source Control and Version Management
Continuous Integration for AI Solutions
Evaluation and Safety Gates
Continuous Delivery and Environment Promotion
Infrastructure as Code
Model and Agent Deployment Automation
Secrets, Identity, and Secure Delivery
Release Strategies
Rollback and Recovery
Release Evidence and Auditability
Lifecycle Operations and Maintenance
Enterprise Deployment Capstone
Summary

24 Enterprise AI Architecture and Design Patterns 16 topics

Enterprise AI Architecture Foundations
Requirements and Workload Analysis
Model and Service Selection
Layered Enterprise AI Architecture
Generative AI Application Patterns
Retrieval-Augmented Generation Architecture
Agentic Architecture Patterns
Workflow and Integration Patterns
State, Memory, and Context Design
Enterprise Data Architecture
Scalability, Performance, and Cost
Reliability and Resilience
Security and Trust Architecture
Architecture Evaluation and Documentation
Enterprise Architecture Workshop
Summary

25 Enterprise AI Case Studies and Solution Workshops 12 topics

Enterprise AI Case Study and Evaluation Method
Case Study One: Enterprise Knowledge Assistant
Case Study Two: Customer-Service Agent
Case Study Three: Intelligent Document Processing
Case Study Four: Multimodal Media Intelligence
Case Study Five: Regulated Decision Support
Case Study Six: Intelligent Business-Process Automation
Cross-Case Comparison
Proof-of-Concept, Pilot, and Implementation Planning
Business Value and Cost Analysis
Enterprise Solution Workshop
Summary

26 AI-103 Certification Review and Final Enterprise Capstone 14 topics

Understanding the AI-103 Certification
Certification Preparation Strategy
Comprehensive AI-103 Domain Review
Service-Selection Decision Framework
Common AI Solution Decision Patterns
Integrated Troubleshooting Review
Scenario-Based Certification Practice
Practice Exam Analysis and Remediation
Final Enterprise Capstone
Capstone Architecture and Implementation
Capstone Testing and Validation
Capstone Documentation and Defense
Final Certification Readiness Assessment
Summary

03 / FAQs

Questions before you start

Is this course suitable for beginners in AI?

While we cover foundations, this course is designed for developers. You should have a baseline understanding of cloud concepts and programming to handle the 102 exercises effectively.

How does this course prepare me for the AI-103 exam?

We align directly with the certification domains, providing 160 practice quizzes and a dedicated capstone review to ensure you understand the service-selection decision framework.

Does this course cover Microsoft Foundry?

Yes, we include dedicated modules on building, operating, and deploying AI agents using Microsoft Foundry, including CI/CD and lifecycle automation.

Are there hands-on labs included?

Absolutely. The course includes 102 practice exercises that force you to apply concepts like RAG, prompt design, and AI monitoring in simulated enterprise environments

Master Azure AI Engineering

Build practical Azure AI skills through hands-on exercises and practice quizzes. Learn generative AI, RAG, AI agents, deployment, and responsible AI.

1 year of full access
Certificate of completion

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