Can the program be customized?

Yes. Develop Generative AI Apps with Azure OpenAI and Semantic Kernel supports customization around lab depth, demo context, certification focus, and team-specific scenarios.

Yes. This program includes instructor-led labs and practical exercises aligned to real implementation patterns.

How does this align with official certification or curriculum?

This program is aligned to the official Official Source curriculum and learning path referenced for this track.

How are prerequisites assessed?

We review prerequisite readiness during scoping and can recommend preparatory modules or a skills checkpoint before cohort start.

What happens after the program?

Private cohorts receive a handover summary, recommended next learning paths, and optional follow-on advisory for rollout or certification readiness.

Enterprise Program Brief

Applied Skills ValidationTrack: Microsoft Applied Skills credential

MicrosoftIntermediate

Develop Generative AI Apps with Azure OpenAI and Semantic Kernel

Applied skill focused on developing generative AI applications with Azure OpenAI and Semantic Kernel using applied implementation tasks.

Duration

Applied skill assessment

Level

Intermediate

Format

Virtual, On-site, or Hybrid

Language

English

Plan Private Delivery Consult a Solutions Architect

Executive brief for stakeholdersDownload Program Brief (PDF)

Enterprise Track

Microsoft

Applied Skill

Semantic Kernel and generative AI apps

Azure OpenAI

ASK

On this page

Ideal for

AI Engineer, DeveloperGenerative AIHands-On Skill ValidationTailored Team Delivery

Microsoft Credential Retired

The official Microsoft Applied Skills assessment for this program has been retired and can no longer be earned. VNode ITeS can still deliver this training content — contact us to discuss your learning objectives.

How VNode delivers this

Who this is for, and how we run it

VNode ITeS delivers Develop Generative AI Apps with Azure OpenAI and Semantic Kernel as an MCT-led Microsoft program for AI Engineer, Developer. Typical duration is Applied skill assessment (Virtual, On-site, or Hybrid). Labs follow production-shaped scenarios rather than slide-only walkthroughs. Applied Skills delivery aims at a working artifact your team can take back, not a quiz score. Private cohorts can shift emphasis by role mix, workspace or repo constraints, and rollout timing.

Audience Profile

Built for these roles

AI engineers and developers building agentic and generative AI applications with Azure OpenAI and Semantic Kernel.

Overview

Executive overview

Official Microsoft Applied Skills credential focused on building generative AI applications with Azure OpenAI and Semantic Kernel.

Readiness

Prerequisites

Working knowledge of C# or Python.
Familiarity with Azure OpenAI fundamentals.
Experience with application development and REST or SDK-based integration.

Program Outcomes

Capabilities your teams will gain

Develop generative AI apps with Azure OpenAI

Use Semantic Kernel for orchestration and AI workflows

Apply implementation skills in a guided assessment-aligned format

Strengthen delivery capability for applied AI delivery

Curriculum

Curriculum roadmap

Azure OpenAI setup and API integration

Semantic Kernel foundations and plugin development

Generative AI workflow and agent design

Evaluation, responsible AI, and production governance

Module 1

Azure OpenAI Setup and Integration

Configure Azure OpenAI resources, manage deployments, and integrate the API into application workflows using SDK and REST patterns.

Configure Azure OpenAI resources
manage deployments
and integrate the API into application workflows using SDK
REST patterns

Module 2

Semantic Kernel Foundations

Build SK-based orchestration with kernel plugins, memory, and planner capabilities for generative AI application workflows.

Build SK-based orchestration with kernel plugins
and planner capabilities for generative AI application workflows

Module 3

GenAI Workflow and Agent Design

Implement agent-style reasoning and task execution workflows using Semantic Kernel patterns aligned to enterprise use cases.

Implement agent-style reasoning
task execution workflows using Semantic Kernel patterns aligned to enterprise use cases

Module 4

Evaluation and Responsible AI

Apply evaluation metrics, safety guardrails, and responsible AI controls for pre-production validation and governance compliance.

Apply evaluation metrics
safety guardrails
and responsible AI controls for pre-production validation
governance compliance

Delivery Models

Delivery models

Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend

Engagement Fit

Engagement fit

Applied skills validationImplementation-focused labsPrivate cohort deliveryIntermediate practitioner depth

Enterprise Customization

Enterprise customization

Tailor this program to your organization's priorities: Helps teams create Azure OpenAI and Semantic Kernel-based applications that move beyond demos into guided implementation.

•Align to your AI agent or assistant use case
•Add enterprise prompt and evaluation guardrails
•Extend into production architecture and governance patterns

Credentials

Certification & official source

•Microsoft Applied Skills credential

Aligned to the official source referenced for this program.

View Official Source

Resources

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.

Program brief (PDF)View Official Source

Enterprise Proof

Trusted delivery outcomes

“We needed a partner who understood both the technical depth of Azure OpenAI and the governance requirements of an enterprise.”

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

Read engagement

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

Read engagement

Delivery Capability

Enterprise-grade instruction

View delivery capability profile

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

Plan delivery