Duration 3 Days – 24 hrs.

 

Overview

 

The Azure OpenAI Training Course is designed to equip professionals with the knowledge and practical skills to build, deploy, and manage AI-powered applications using Microsoft Azure’s OpenAI services.

 

Participants will learn how to leverage large language models (LLMs), including GPT-based models, within a secure and scalable Azure environment. The course covers prompt engineering, API integration, responsible AI practices, and real-world use cases such as chatbots, automation, and data analysis.

 

This training emphasizes hands-on implementation, enabling participants to develop enterprise-ready AI solutions aligned with business and compliance requirements.

 

Objectives

 

• Understand the fundamentals of Generative AI and Large Language Models (LLMs)
• Navigate and configure Microsoft Azure for AI workloads
• Use Azure OpenAI Service to access and deploy OpenAI models
• Design effective prompts for various business use cases
• Build AI-powered applications (chatbots, summarization tools, automation workflows)
• Integrate Azure OpenAI APIs into web and enterprise systems
• Implement responsible AI practices, security, and compliance controls
• Optimize performance, cost, and scalability of AI solutions

 

Target Audience

 

• Software Developers and Engineers
• Data Analysts and Data Scientists
• AI/ML Engineers and Architects
• IT Managers and Technical Leads
• Business Analysts and Digital Transformation Teams
• Innovation and Product Development Teams

 

Prerequisites

 

• Basic understanding of programming (Python, JavaScript, or similar)
• Familiarity with APIs and REST services
• Basic knowledge of cloud computing concepts (preferred)
• No prior AI experience required (introductory concepts included)

 

Course Outline

 

Module 1: Introduction to Generative AI and Azure OpenAI

 

• Overview of Generative AI and LLMs
• Introduction to GPT models and capabilities
• Use cases in enterprise environments
• Overview of Azure OpenAI architecture

 

Module 2: Getting Started with Azure OpenAI

 

• Setting up Azure subscription and resources
• Accessing Azure OpenAI Service
• Understanding model deployments and endpoints
• Managing API keys and authentication

 

Module 3: Prompt Engineering Fundamentals

 

• Principles of effective prompting
• Zero-shot, one-shot, and few-shot prompting
• Prompt patterns for business scenarios
• Handling hallucinations and improving output quality

 

Module 4: Building Applications with Azure OpenAI

 

• Using REST APIs and SDKs
• Creating chatbots and conversational interfaces
• Text generation, summarization, and classification
• Integrating with web apps and enterprise systems

 

Module 5: Advanced Capabilities and Integration

 

• Embeddings and semantic search
• Retrieval-Augmented Generation (RAG)
• Integration with Azure services (e.g., storage, functions, databases)
• Automating workflows using AI

 

Module 6: Responsible AI, Security, and Compliance

 

• Responsible AI principles
• Content filtering and moderation
• Data privacy and governance in Azure
• Risk management in AI deployments

 

Module 7: Performance Optimization and Cost Management

 

• Token usage and cost considerations
• Performance tuning techniques
• Monitoring and logging AI applications
• Scaling AI workloads in Azure

 

Module 8: Hands-On Capstone Project

 

• Design and build a real-world AI solution
  (e.g., AI chatbot, document analyzer, or automation tool)
• End-to-end implementation using Azure OpenAI
• Presentation and evaluation of solutions