“We needed a partner who understood both the technical depth of Azure OpenAI and the governance requirements of an enterprise.”
Enterprise Program Brief
VNode ITeSBeginner
Azure OpenAI & Generative AI Fundamentals
This program introduces Azure OpenAI Service, core LLM capabilities, and enterprise application patterns. Participants move beyond theory by deploying Azure-hosted GPT models, writing effective prompts for real tasks, and understanding governance requirements for responsible AI in production.
Duration
3 days
Level
Beginner
Format
Virtual or On-site
Language
English
Executive brief for stakeholdersDownload Program Brief (PDF)
AOAI
AI
On this page
Ideal for
Tailored Team DeliveryImplementation-Focused
Audience Profile
Built for these roles
Developers, architects, and technical leads exploring enterprise AI adoption
Overview
Executive overview
Deploy Azure OpenAI, apply prompt engineering fundamentals, and understand governance requirements for enterprise AI.
Readiness
Prerequisites
- Basic programming experience (Python or C#)
- Familiarity with Azure fundamentals or equivalent cloud exposure
Program Outcomes
Capabilities your teams will gain
Deploy and call Azure OpenAI endpoints via SDK
Apply prompt engineering techniques across common enterprise tasks
Understand model selection trade-offs (GPT-4o, GPT-4, embedding models)
Address AI ethics, data privacy, and responsible AI requirements
Curriculum
Curriculum roadmap
1
Azure OpenAI Service overview and deployment
2
GPT-4o capabilities and model selection
3
Prompt engineering for enterprise tasks
4
AI ethics, governance, and responsible AI
1Module 1
Azure OpenAI Service
+
Module 1
Azure OpenAI Service
Deploy and configure Azure OpenAI endpoints, understand the model catalog and quota management, and call GPT-4o via SDK for enterprise AI scenarios.
- configure Azure OpenAI endpoints
- understand the model catalog
- quota management
- and call GPT-4o via SDK for enterprise AI scenarios
2Module 2
GPT-4o and Prompt Engineering
+
Module 2
GPT-4o and Prompt Engineering
Apply systematic prompt engineering techniques for real-world business tasks using zero-shot, few-shot, and chain-of-thought patterns.
- Apply systematic prompt engineering techniques for real-world business tasks using zero-shot
- and chain-of-thought patterns
3Module 3
AI Ethics and Governance
+
Module 3
AI Ethics and Governance
Address responsible AI requirements, data privacy, content filtering, and enterprise usage policies for compliant AI deployment.
- Address responsible AI requirements
- data privacy
- content filtering
- and enterprise usage policies for compliant AI deployment
4Module 4
Enterprise Deployment Basics
+
Module 4
Enterprise Deployment Basics
Integrate Azure OpenAI into applications via SDK, manage quotas and endpoints, and design a production-ready deployment architecture.
- Integrate Azure OpenAI into applications via SDK
- manage quotas
- and design a production-ready deployment architecture
Delivery Models
Delivery models
Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend
Engagement Fit
Engagement fit
Implementation-focused labsPrivate cohort deliveryBeginner practitioner depthBusiness outcome alignment
Enterprise Customization
Enterprise customization
Tailor this program to your organization's priorities: Gives technical teams a grounded foundation in Azure AI services before committing to production AI investments.
- •Industry-specific use cases (finance, healthcare, retail, manufacturing)
- •Python or C# SDK focus based on team preference
- •Extended responsible AI governance module
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.
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
