“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: Azure AI Engineer Associate
MicrosoftIntermediate
Azure AI Engineer Associate
AI-102 focuses on developing AI solutions in Azure, including generative AI applications, intelligent agents, natural language, computer vision, and information extraction workloads.
Duration
2 to 4 days
Level
Intermediate
Format
Virtual, On-site, or Hybrid
Language
English
Executive brief for stakeholdersDownload Program Brief (PDF)
In Demand
Microsoft
AI Solutions EngineeringIT
Azure AI Engineer Associate
Azure AI
AI
On this page
Ideal for
AI EngineerAI Solutions EngineeringCertification ReadinessTailored Team Delivery
How VNode delivers this
Who this is for, and how we run it
VNode ITeS delivers Azure AI Engineer Associate as an MCT-led Microsoft program for AI Engineer. Typical duration is 2 to 4 days (Virtual, On-site, or Hybrid). Labs follow production-shaped scenarios rather than slide-only walkthroughs. Certification prep maps to AI-102T00 without turning the week into a dump of Learn modules. Private cohorts can shift emphasis by role mix, workspace or repo constraints, and rollout timing.
Audience Profile
Built for these roles
Built for AI engineers and developers building production AI solutions on the Azure AI platform.
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
- Hands-on experience in the relevant Microsoft workload area.
- Familiarity with core product concepts and enterprise delivery expectations.
Program Outcomes
Capabilities your teams will gain
Strengthen readiness for AI-102 certification objectives
Build deeper delivery capability in ai solutions engineering scenarios
Prepare teams for more confident project execution in the target Microsoft workload
Support structured certification-led upskilling across the organization
Curriculum
Curriculum roadmap
1
Azure AI solution planning, management, and security
2
Computer vision and document intelligence solutions
3
Natural language processing and speech AI solutions
4
Knowledge mining, Azure AI Search, and document intelligence
5
Generative AI solutions with Azure OpenAI and responsible AI
1Module 1
Azure AI Solution Planning and Management
+
Module 1
Azure AI Solution Planning and Management
Provision and manage Azure AI Services resources, configure authentication and security, implement responsible AI practices, and monitor AI solution health and performance.
- manage Azure AI Services resources
- configure authentication
- implement responsible AI practices
- and monitor AI solution health
2Module 2
Computer Vision and Document Intelligence
+
Module 2
Computer Vision and Document Intelligence
Build computer vision solutions using Azure AI Vision for image classification, object detection, OCR, and spatial analysis. Process documents with Azure Document Intelligence and custom models.
- Build computer vision solutions using Azure AI Vision for image classification, object detection, OCR, and spatial analysis
- Process documents with Azure Document Intelligence and custom models
3Module 3
Natural Language Processing and Speech
+
Module 3
Natural Language Processing and Speech
Implement NLP solutions using Azure AI Language for text analytics, entity recognition, question answering, and conversational AI. Build speech-to-text and text-to-speech pipelines.
- Implement NLP solutions using Azure AI Language for text analytics, entity recognition, question answering, and conversational AI
- Build speech-to-text and text-to-speech pipelines
4Module 4
Knowledge Mining and Azure AI Search
+
Module 4
Knowledge Mining and Azure AI Search
Design knowledge mining solutions using Azure AI Search with indexers, custom skillsets, enrichment pipelines, and semantic search for intelligent enterprise search scenarios.
- Design knowledge mining solutions using Azure AI Search with indexers
- custom skillsets
- enrichment pipelines
- and semantic search for intelligent enterprise search scenarios
5Module 5
Generative AI with Azure OpenAI
+
Module 5
Generative AI with Azure OpenAI
Build generative AI solutions using Azure OpenAI service, implement prompt engineering, design RAG architectures, and apply content filtering and responsible AI governance controls.
- Build generative AI solutions using Azure OpenAI service
- implement prompt engineering
- design RAG architectures
- and apply content filtering
- responsible AI governance controls
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
- •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