Azure OpenAI Service: Implementation & Architecture

Duration 4 hours
Level Builder
Focus Areas
Vendor
Learning Track

Enterprise Platforms & AI Architecture

Part of the Enterprise Platforms & AI Architecture track, built for IT leaders, architects, and technical teams standing up Microsoft platforms, data models, and AI governance across the business.

View the full Enterprise Platforms & AI Architecture track →

Overview & Learning Objectives

A technical architecture session on provisioning, securing, and integrating Azure OpenAI Service into enterprise applications and corporate data.

By the end of this training, participants will be able to:

  • Provision Azure OpenAI resource instances, deploy models (GPT-4o, Embeddings), and manage API quotas.
  • Connect Azure OpenAI securely to proprietary enterprise data using RAG (Retrieval-Augmented Generation).
  • Implement Azure AI Content Safety filters, Role-Based Access Control (RBAC), and private endpoints.
  • Build a functional enterprise AI pilot application integrated into an existing business workflow.

Target Audience

  • Developers, enterprise architects, and cloud engineers
  • Technical managers and innovation leads designing secure AI infrastructure

Prerequisites

  • Understanding of basic cloud architecture and web application concepts
  • Familiarity with Azure portal navigation, REST APIs, or application integration

Technical Requirements

  • Active Azure subscription with Azure OpenAI Service access enabled (provisioned deployment key and endpoint URL).

Format & Customization Options

Format of the Course

  • Interactive lecture and live architecture demonstration.
  • Guided hands-on API implementation in a sandbox Azure environment.

Course Customization Options

  • Custom enterprise landing zone architecture and SDK language modules (Python, C#, JS) available upon request.

Azure OpenAI Service: Implementation & Architecture - Inquiry

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