MS-AI103.KZ1 ISBN: 979-8-90059-163-6
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.
What you will be able to do
- 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.
Intermediate A tu propio ritmo · 1 año de acceso
55 LiveLabs prácticos
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01 / About
Acerca de este curso
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No se requiere tarjeta de crédito
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.
02 / Lecciones y laboratorios
See exactly what you will learn and practice
Plan de estudios
26 Lecciones interactivas · 259 topics01 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 · 2 Laboratorio en vivo +
- 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
2 Laboratorio en vivo in this lesson — see the labs panel →
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 · 3 Laboratorio en vivo +
- 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
3 Laboratorio en vivo in this lesson — see the labs panel →
06 Developing AI Applications with Azure OpenAI Service 9 topics · 5 Laboratorio en vivo +
- Azure OpenAI Development Environment
- 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
5 Laboratorio en vivo in this lesson — see the labs panel →
07 Prompt Engineering and AI Interaction Design 11 topics · 4 Laboratorio en vivo +
- Azure OpenAI Service Architecture
- 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
4 Laboratorio en vivo in this lesson — see the labs panel →
08 Retrieval-Augmented Generation (RAG) with Azure AI Search 10 topics · 6 Laboratorio en vivo +
- 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
6 Laboratorio en vivo in this lesson — see the labs panel →
09 Developing AI Agents with Microsoft Foundry 9 topics · 7 Laboratorio en vivo +
- 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
7 Laboratorio en vivo in this lesson — see the labs panel →
10 Implementing Computer Vision Solutions with Azure AI Vision 11 topics · 2 Laboratorio en vivo +
- Introduction to Computer Vision
- Azure AI Vision Resources
- Image Analysis
- Optical Character Recognition (OCR)
- Image Embeddings and Visual Search
- Generative Image and Video Solutions
- Multimodal AI Applications
- Building Enterprise Vision Applications
- Security, Responsible AI, and Optimization
- End-to-End Computer Vision Solutions
- Summary
2 Laboratorio en vivo in this lesson — see the labs panel →
11 Implementing Natural Language Processing Solutions with Azure AI Language 10 topics · 4 Laboratorio en vivo +
- Introduction to Natural Language Processing
- 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
4 Laboratorio en vivo in this lesson — see the labs panel →
12 Implementing Speech AI Solutions with Azure AI Speech 10 topics · 1 Laboratorio en vivo +
- 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
1 Laboratorio en vivo in this lesson — see the labs panel →
13 Implementing Document Intelligence Solutions with Azure AI Document Intelligence 11 topics · 3 Laboratorio en vivo +
- 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
3 Laboratorio en vivo in this lesson — see the labs panel →
14 Building Multimodal AI Applications with Microsoft Foundry 10 topics · 1 Laboratorio en vivo +
- 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
1 Laboratorio en vivo in this lesson — see the labs panel →
15 Building and Operating AI Solutions with Microsoft Foundry 9 topics · 2 Laboratorio en vivo +
- 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
2 Laboratorio en vivo in this lesson — see the labs panel →
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 · 3 Laboratorio en vivo +
- 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
3 Laboratorio en vivo in this lesson — see the labs panel →
18 Responsible AI, Governance, Risk, and Compliance for Azure AI Solutions 10 topics · 2 Laboratorio en vivo +
- 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
2 Laboratorio en vivo in this lesson — see the labs panel →
19 Enterprise AI Reference Architectures and Solution Patterns 10 topics · 1 Laboratorio en vivo +
- 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
1 Laboratorio en vivo in this lesson — see the labs panel →
20 Security, Identity, Networking, and Keyless Access 10 topics · 1 Laboratorio en vivo +
- 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
1 Laboratorio en vivo in this lesson — see the labs panel →
21 Monitoring, Drift, Grounding Quality, and Search Health 10 topics · 3 Laboratorio en vivo +
- 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
3 Laboratorio en vivo in this lesson — see the labs panel →
22 Governance, Control, and Auditability of AI Agents 10 topics · 2 Laboratorio en vivo +
- 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
2 Laboratorio en vivo in this lesson — see the labs panel →
23 Microsoft Foundry Deployment, CI/CD, and Lifecycle Automation 16 topics · 1 Laboratorio en vivo +
- 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
1 Laboratorio en vivo in this lesson — see the labs panel →
24 Enterprise AI Architecture and Design Patterns 16 topics · 2 Laboratorio en vivo +
- 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
2 Laboratorio en vivo in this lesson — see the labs panel →
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
Laboratorios prácticos Our edge
55 Laboratorio en vivos- Setting Up a Microsoft Foundry Development Environment
- Deploying and Testing Foundation Models in Microsoft Foundry
- Planning Azure AI Resources, Quotas, Scaling, and Cost Optimization
- Architecting Enterprise Azure AI Integration
- Choosing the Right AI Model, Service, and Architecture
- Building Your First AI Application with the Microsoft Foundry SDK
- Integrating Azure OpenAI with SDKs, REST APIs, and Streaming
- Building Enterprise Chat Applications with Azure OpenAI
- Hardening Enterprise Azure OpenAI Deployments
- Building AI Applications with Function Calling and Tool Integration
- Applying Prompt Engineering Fundamentals Using the Microsoft Foundry SDK
- Evaluating Generative AI Responses with Microsoft Foundry
- Optimizing Prompts and Generating Structured Outputs
- Optimizing Enterprise Prompt Architecture
- Architecting Enterprise Retrieval-Augmented Generation
- Building and Optimizing an Azure AI Search Ingestion and Retrieval Pipeline
- Creating Embeddings and Semantic Search Pipelines
- Building an Enterprise RAG Application with Azure AI Search and Python
- Evaluating Grounding Quality, Retrieval Performance, and Hallucination Detection
- Choosing Between Fine-Tuning and RAG for Enterprise AI Solutions
- Building AI Agents with Microsoft Foundry Agent Service
- Configuring Agent Instructions, Threads, Runs, and Conversation State
- Building Agents with File Search and Code Interpreter
- Building Multi-Agent Orchestration Workflows
- Architecting Autonomous Agent Security Governance
- Monitoring, Evaluating, and Debugging AI Agents
- Integrating OpenAPI Tools and External APIs
- Remediating Azure AI Vision Failures
- Implementing Image Analysis, OCR, Object Detection, and Visual Search
- Building Natural Language Processing Solutions with Azure AI Language
- Implementing Entity Extraction, Summarization, Translation, and Structured JSON Generation
- Building Conversational Language Understanding Applications
- Defending Granular NLP Pipeline Architecture
- Implementing Speech-to-Text and Speech Translation
- Processing Documents with Azure AI Document Intelligence
- Building Intelligent Document Processing Pipelin... OCR, Layout Analysis, and Content Understanding
- Architecting Multimodal Fraud Ingestion Pipelines
- Building Multimodal AI Applications with Visual Understanding
- Architecting Enterprise Foundry Integration Patterns
- Evaluating AI Application Safety and Comparing Model Performance
- Enterprise API Integration, Azure API Management, and Secure AI Services
- Deploying Serverless and Event-Driven AI Applications
- Defending Decoupled Enterprise AI Architecture
- Implementing Responsible AI Guardrails, Prompt S...tion, Groundedness Detection, and Content Safety
- Responsible AI Pre-Deployment Risk Evaluation
- Defending Enterprise Azure AI Architecture
- Securing Azure AI with Managed Identity, RBAC, Private Networking, and Keyless Authentication
- Grounding Audit Remediation Defense
- Monitoring AI Application Performance, Grounding Quality, and Quality Drift
- Observability, Tracing, Token Analytics, and Performance Optimization
- Governing AI Agents with Tool Restrictions, Audit Logging, and Execution Provenance
- Enterprise Agent Governance Architecture Defense
- Architecting Keyless Pipeline Identity
- Designing Secure, Scalable, and Cost-Optimized Enterprise AI Solutions
- Designing Enterprise AI Architecture for RAG, Agents, and Multimodal Systems
Los laboratorios se ejecutan en tu navegador; no hay nada que instalar.
03 / Preguntas frecuentes
Preguntas antes de empezar
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 año de acceso completo
- 55 LiveLab incluido
- Certificado de finalización
No se requiere tarjeta de crédito