AI-102 Azure AI Engineer: OpenAI, Vision, Language & Agents

Build AI solutions using Azure OpenAI, Vision, Language, Speech, AI Search, Agents, and Semantic Kernel

Created bySandeep Soni

Last updated 3/2026

English

English [Auto],

What you'll learn

Design AI solutions using Azure AI services
Build applications using Azure OpenAI models
Provision and configure Azure AI resources
Integrate AI services using REST APIs and SDKs
Build natural language processing solutions
Implement speech recognition and synthesis

Course content

10 sections • 42 lectures • 21h 50m total length

Introduction25:17
Explore how Azure cloud platform delivers ready-made cognitive services and AI models to build modern intelligent applications via REST APIs, covering language, speech, vision, and AI search.
Provisioning Azure AI Services14:03
Provision Azure AI language service resources and create a language service instance with optional fine-tuning. Use the free tier, manage endpoints and keys, rotate without downtime, and apply RBAC.
Provisioning Azure AI Services Part 224:04
Learn to provision Azure AI Vision and language services, choose between single and multi-service resources, and manage them under an Azure AI Foundry resource with default projects, endpoints, and permissions.
Using REST API17:22
Learn to access Azure AI cognitive services with REST API, obtain endpoints and keys, and build a console app in C#, then compare REST with SDK workflows.
Using AI Services SDK8:11
Use Azure AI service SDKs across languages (.NET, Python, Node.js, Java) for text analytics and sentiment, compare with REST API, and explore text-to-speech setup.

Working with OpenAI Models26:38
Learn to deploy OpenAI models in Azure with AI Foundry, creating deployments from base or fine-tuned models, and manage deployment types, data residency, and model routing for GPT 5.
Authenticating and Executing Prompt18:38
Learn to build an Azure OpenAI SDK app, authenticate with key, intra-id, or managed identities, and configure a chat client for a modal deployment and endpoint.
Using OpenAI Models15:45

Introduction to AI Foundry Portal19:03
Explore the Azure AI Foundry portal to manage projects, resources, service connections, and model deployment, testing, and governance through prompt flows, vector indexing, and RBAC.
Types of Projects35:08
About AI Foundry Model26:20
Navigate the Azure AI Foundry model catalogue to discover, compare, and deploy models from multiple vendors, and learn to choose foundation and domain-specific options with serverless or managed compute deployment.
Create AI Projects and Provisioning Model Deployments36:04
Design and launch AI projects by provisioning model deployments using Azure AI tools, integrating OpenAI, vision, language and agents capabilities.
Using Foundry Models in Code31:00
Summary of Connections between Projects and Resources31:00

Analyzing Caption, Dense Caption and Tags27:07
Analysing Objects10:32
Detect objects in the vision portal, view bounding boxes, tags, and confidence scores, and learn to annotate images using visualFeatures.object.
Analyzing for People and Smartcrops16:43
Reading Text from Image OCR10:23
Read text from images using optical character recognition, converting handwritten and printed text into a digitized document. Explore json with a lines array and bounding rectangle data.
Use Case of AI6:50
Custom Vision Training and Prediction43:18
Explore custom vision training and prediction in the Azure AI Engineer course, focusing on building and evaluating models with vision services.
Face API44:48
Explore the face API as part of the azure ai engineer course on OpenAI, vision, language, and agents.

Text Analytics26:13
Text Translate22:58
Discover Azure's text translation service, which detects language, translates to multiple target languages, and transliterates scripts, with endpoints, options, and required key and region configuration.
Custome Question Answer Service33:32
Develop a custom question answering service by leveraging Azure AI Engineer capabilities, integrating OpenAI models, Vision, Language, and agents for end-to-end QA solutions.
Conversational Languages Understanding50:28
Explore conversational language understanding within the Azure AI Engineer course, highlighting OpenAI, vision, language, and agents.

Introduction to Search Service30:16
Explore Azure AI search to create a knowledge base by indexing data from multiple data sources with an indexer and cognitive skills, including vectorization and scalable replicas and partitions.
Importing Data from Data Source into Index Using Indexer and Skillset32:08
Master the enrichment pipeline to import data into Azure search using data sources, skill sets (language detection, OCR, merge), and an indexer to build and query the index.
Explore and modify definitions of search components17:14
Learn to inspect and modify Azure search components by editing index, indexer, and skill set json, adding sentiment and url fields and configuring field mappings.
Building a search client27:05
Build a practical search client in a C# console app using Azure search, configure appsettings, query an index, apply filters, and customize results with a typed document.
Building a Custom Skill to skillset28:34
Build a custom skill for Azure AI search with an HTTP triggered function app and custom web API, mapping word count to the index, optionally using OpenAI.
Creating knowledge store29:15

Overview of Agentic AI Framework1:05:27
Explore the agentic AI framework within the Azure AI Engineer context, showing how OpenAI, vision, language, and agents integrate to power capable intelligent systems.
Agentic Prompt31:41
Options for Agent Development3:33
Explore agent development options from low-code platforms like Co-Pilot Studio and Microsoft 365 agent SDKs to frameworks such as Semantic Kernel, Autogen, and LangChain.

Get Started with AI Agent Development on Azure Part 154:17
Begin building AI agents on Azure by exploring fundamentals of agent development, tooling, and workflows, with a focus on integrating OpenAI capabilities for vision, language, and autonomous actions.
Get Started with AI Agent Development on Azure Part 246:11
Building your Frist AI Agent: C# and Python QuickStarts54:23
Build your first AI agent using C# and Python quickstarts, guided by Azure AI Engineer concepts for OpenAI, Vision, Language, and Agents.
Working with Tools in Azure AI Foundry Agent Service1:57:46
Explore how to work with tools in the Azure AI Foundry agent service to enhance capabilities for building and deploying agents in the AI engineer ecosystem.

Introduction to Semantic Kernel9:12
Explore semantic kernel, a lightweight open-source framework to build enterprise agents. Orchestrate plugins, vectorization, and LLMs across C#, Python, and Java with secure telemetry and rapid workflow automation.
Getting started with Semantic Kernel1:33:34
Get started with semantic kernel to connect language, tools, and agents within Azure AI engineer workflows, leveraging OpenAI capabilities.

Requirements

Basic knowledge of cloud computing
Familiarity with Azure fundamentals
Basic programming knowledge in C# or Python
Understanding of REST APIs

Description

This course prepares developers and AI engineers to design and implement AI solutions on Microsoft Azure while preparing for the AI-102 Designing and Implementing a Microsoft Azure AI Solution certification.

Modern applications increasingly rely on artificial intelligence to understand language, analyze images, generate content, and automate complex workflows. In this course, you will learn how to build intelligent applications using Azure AI services, including Azure OpenAI Service, Azure AI Vision, Azure AI Language, and Azure AI Speech.

You will start by understanding Azure AI services architecture and how to provision and interact with these services using REST APIs and SDKs. The course then explores OpenAI models in Azure, including prompt execution and application integration.

You will also work with the Azure AI Foundry platform, where you will learn how to create AI projects, deploy models, and build applications that connect AI resources and services.

The course then covers real-world AI workloads such as computer vision, natural language processing, speech recognition, and knowledge mining using Azure AI Search. You will also explore modern AI application architectures including agent-based AI systems and orchestration frameworks like Semantic Kernel.

By the end of this course, you will be able to design and implement production-ready AI solutions on Azure, making it ideal for developers preparing for the AI-102 certification and professionals building enterprise AI applications.

Who this course is for:

Developers building AI applications
Azure AI Engineers
Cloud engineers working with Azure AI
Software engineers implementing AI solutions
Professionals preparing for the AI-102 certification

AI-102 Azure AI Engineer: OpenAI, Vision, Language & Agents

What you'll learn

Explore related topics

Course content

Azure AI Introduction5 lectures • 1hr 29min

Working with OpenAI Models3 lectures • 1hr 1min

Azure AI Foundry6 lectures • 2hr 59min

Vision Service7 lectures • 2hr 40min

Azure AI Language Service4 lectures • 2hr 13min

Azure AI Speech2 lectures • 48min

Knowledge Mining6 lectures • 2hr 45min

Foundations and Agent Development3 lectures • 1hr 41min

Azure AI Foundry Agent Service4 lectures • 4hr 33min

Semantic Kernel2 lectures • 1hr 43min

Requirements

Description

Who this course is for: