Module Overview

Overview

Azure OpenAI Service provides REST API access to OpenAI's powerful language models including the GPT-3, Codex and Embeddings model series. In this course you will learn to use these models including GPT -3, GPT -4 which performs a variety of natural language tasks, Codex, which translates natural language to code, and Embeddings, which is an information dense representation of the semantic meaning of a piece of text. Start building with simple API calls and get started with it in a matter of minutes!

Course Modules

Modules

Understand Azure AI Foundry - The AI app and agent factory

In this module, you will learn about Introduction to Azure AI services and LLMs​, Azure OpenAI Service​, Introduction to Responsible AI​, Components and key concepts of Azure OpenAI​, Models and Capabilities​, Azure AI Studio​, managing models​, Provisioned throughput units (PTU)​, Using function calling with Azure OpenAI Service (Preview)​, Azure OpenAI Assistants API (Preview)​, Availability and pricing​.

AI Development and Agentic DevOps with GitHub

In this module, you will learn about Introduction to prompt engineering​, Prompt engineering techniques​, Understanding embeddings in Azure OpenAI Service​, Plugins, ​ Azure AI Search​, Full text search, ​Vector search, Semantic ranking​, Retrieval augmented generation – RAG, Semantic Kernel​.

Customize Gen AI Apps and agents at scale

Customize a model with fine-tuning, Using Azure OpenAI with large datasets​, Using your data - text​, Using your data - image(preview)​, Prompt flow and LLMOps​.

Fine-tune models with Azure AI Foundry

Introduction to Abuse monitoring, Content filtering, Content Filtering in Azure AI Studio​ Data, privacy, and security for Azure OpenAI Service​, Configuring Azure OpenAI Service with Managed Identities and Azure Cognitive Services virtual networks​, Manage quota​, Azure OpenAI Service encryption of data at rest​, Monitoring Azure OpenAI Service​, Planning to manage costs for Azure OpenAI Service​, Responsible AI principles and practices for Azure OpenAI​.

Develop agents with Azure OpenAI

Revisit Azure OpenAI capabilities, exploring models available in the Azure AI Foundry catalog and integrating your own data for tailored experiences. Learn to implement function calling, Azure OpenAI Assistants, Retrieval Augmented Generation (RAG), fine-tuning, and optimize deployments using provisioned AOAI Services (PTUs).

Build multi agent apps with Semantic Kernel or AutoGen

Explore multi-agent orchestration by leveraging Semantic Kernel and AutoGen frameworks to build intelligent, collaborative agent systems. Understand how these frameworks enable task coordination, context sharing, and scalable AI-driven workflows.

Monitor, secure and govern your AI solutions with Azure AI Foundry

Build generative AI workloads aligned with the Well-Architected Framework while applying Responsible AI principles and mitigation layers within Azure AI Foundry. Ensure safety and governance through Azure AI Content Safety, observability tools, risk evaluations, continuous monitoring, Red Teaming Agents, Entra ID integration, and Microsoft Purview compliance.

Post-training Skills Assessment

Take this assessment to validate your skills gathered from the self-paced online learning course completed in this course to mark your completion.

Evaluación de habilidades posteriores a la capacitación - ES

Realice esta evaluación para validar las habilidades adquiridas mediante el aprendizaje en línea a su propio ritmo, como parte del curso, y así marcar su finalización.

培训后技能评估 - ZHCN

参加此评估以验证您从本课程的自定进度在线学习中收集的技能,以标记您的完成情况。

培訓後技能評估 - ZHTW

參加此評估以驗證您從本課程的自定進度線上學習中收集的技能,以標記您的完成情況。

Avaliação de Competências Pós-Formação - PT

Faça esta avaliação para validar suas habilidades adquiridas com o aprendizado online individualizado realizado neste curso para marcar sua conclusão.

トレーニング後のスキル 評価 - JA

この 評価を受けて、このコースで完了した自分の ペースの   オンライン 学習から得たスキルを検証し、完了を 記録    します。

교육 후 기술 평가 - KO

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