“We needed a partner who understood both the technical depth of Azure OpenAI and the governance requirements of an enterprise.”
Enterprise Program Brief
Role-Based Certification PrepTrack: Microsoft Certified: Azure AI Engineer Associate
MicrosoftIntermediate
Develop AI Solutions in Azure
AI-102 focuses on developing AI solutions in Azure, including generative AI applications, intelligent agents, natural language, computer vision, and information extraction workloads.
Duration
5 days
Level
Intermediate
Format
Virtual, On-site, or Hybrid
Language
English
Executive brief for stakeholdersDownload Program Brief (PDF)
In Demand
Microsoft
AI Engineer TrackAI
Foundry, agents, language, vision
Azure AI
AI102
On this page
Ideal for
AI EngineerArtificial IntelligenceCertification ReadinessTailored Team Delivery
Audience Profile
Built for these roles
Software engineers building AI-powered applications with Azure AI Foundry and Azure AI services.
Overview
Executive overview
Official Microsoft Learn course aligned to Azure AI engineering responsibilities, covering generative AI apps, agents, computer vision, language, and information extraction scenarios.
Readiness
Prerequisites
- Experience with C# or Python.
- Familiarity with REST-based APIs and SDK usage.
- Working knowledge of Azure fundamentals and application development.
Program Outcomes
Capabilities your teams will gain
Develop AI-infused applications by using Azure AI services
Build generative AI applications and agent-based solutions
Implement natural language and speech-enabled experiences
Create information extraction and search-driven AI workflows
Curriculum
Curriculum roadmap
1
Azure AI services setup, configuration, and security
2
Computer vision and multimodal AI capabilities
3
Natural language processing and speech solutions
4
Azure AI Search and information extraction
5
Generative AI applications and intelligent agents
1Module 1
Get Started with Azure AI Services
+
Module 1
Get Started with Azure AI Services
Configure, secure, and monitor Azure AI services, including resource provisioning, authentication, and responsible AI controls.
- and monitor Azure AI services
- including resource provisioning
- authentication
- and responsible AI controls
2Module 2
Computer Vision and Multimodal AI
+
Module 2
Computer Vision and Multimodal AI
Build vision-enabled applications with Azure AI Vision, Video Indexer, and multimodal model capabilities for image and video understanding.
- Build vision-enabled applications with Azure AI Vision
- Video Indexer
- and multimodal model capabilities for image
- video understanding
3Module 3
Natural Language Processing and Speech
+
Module 3
Natural Language Processing and Speech
Implement NLP solutions including text analysis, translation, and conversational language; add speech-to-text and text-to-speech capabilities.
- Implement NLP solutions including text analysis
- and conversational language; add speech-to-text
- text-to-speech capabilities
4Module 4
Azure AI Search and Information Extraction
+
Module 4
Azure AI Search and Information Extraction
Design AI-enriched search pipelines with Azure AI Search for knowledge mining, extraction, and intelligent document processing.
- Design AI-enriched search pipelines with Azure AI Search for knowledge mining
- and intelligent document processing
5Module 5
Generative AI and Intelligent Agents
+
Module 5
Generative AI and Intelligent Agents
Build generative AI applications with Azure OpenAI, design agent workflows with Semantic Kernel, and apply evaluation and governance practices.
- Build generative AI applications with Azure OpenAI
- design agent workflows with Semantic Kernel
- and apply evaluation
- governance practices
Delivery Models
Delivery models
Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend
Engagement Fit
Engagement fit
Certification readinessImplementation-focused labsPrivate cohort deliveryIntermediate practitioner depth
Enterprise Customization
Enterprise customization
Tailor this program to your organization's priorities: Helps engineering teams move from AI experimentation to production by building delivery skills in Azure AI application design, development, and deployment.
- •Align labs to your AI use case and domain data
- •Add deeper agent engineering and orchestration coverage
- •Extend into production governance and evaluation workflows
Credentials
Certification & official source
- •Microsoft Certified: Azure AI Engineer Associate
Aligned to the official source referenced for this program.
View Official SourceResources
Program resources
Yes. Most enterprise clients prefer private delivery scoped to role mix, timezone, and rollout timeline. We align lab environments and scenarios to your tenant context where applicable.
Enterprise Proof
Trusted delivery outcomes
Retail & E-commerce
Representative Retail Analytics Team
Instead of treating reporting as a tooling issue alone, the work focused on consistency, governance, and shared delivery practices across analysts and engineering teams.
- Higher consistency in report design practices
- Improved collaboration between analysts and engineering teams
Healthcare
Representative Healthcare Product Team
The engagement helped product and engineering stakeholders move from interest in AI to clearer implementation choices, security expectations, and prototyping discipline.
- Stronger alignment between product and engineering teams
- Improved clarity on prototype-to-production requirements
Delivery Capability
Enterprise-grade instruction
MCT-led delivery
Programs led by Microsoft Certified Trainer practitioners
Enterprise program oversight
Founder-led specialist delivery with structured rollout planning
Global delivery
APAC · EMEA · Americas · Virtual & Onsite
Implementation-focused
Hands-on labs aligned to production scenarios
