AI-200 Study Guide | Developing AI Cloud Solutions on Azure

AI-200 Study Guide Developing AI Cloud Solutions on Azure -2

AI-200 Preparation Details

Preparing for the AI-200 Developing AI Cloud Solutions on Azure certification exam? Start here with a complete, objective-wise AI-200 study guide designed to help you pass faster.

This guide brings together official Microsoft documentation, key concepts, and curated resources for every AI-200 exam objective, making it ideal for both beginners and last-minute revision.

Looking for the best AI-200 preparation resources in one place? This page covers everything you need to get exam-ready with confidence.

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AI-200 Cloud AI Materials

UdemyAzure AI Cloud Developer Associate – Complete Course
CourseraBuilding AI Cloud Apps with Microsoft Azure

Develop containerized solutions on Azure (20–25%)

Implement container application hosting

Build, store, version, and manage container images by using Azure Container Registry

Introduction to Azure Container Registry

Push and pull container images in Azure Container Registry

Container image lock and version management in Azure Container Registry

Build and run images by using Azure Container Registry Tasks

Automate container image builds with Azure Container Registry Tasks

Tutorial: Build and deploy container images with Azure Container Registry Tasks

YAML reference for ACR Tasks

Deploy containers to Azure App Service, including configuring App Service to supply environment variables and secrets

Deploy and run a containerized app in Azure App Service

Configure environment variables and app settings in Azure App Service

Configure a custom container for Azure App Service

Implement container-orchestrated solutions

Deploy applications to Azure Container Apps, including environment configuration and revision management

Deploy your first container app using the Azure portal

Manage revisions in Azure Container Apps

Deploy and Manage Apps on Azure Container Apps – Training

Implement event-driven scaling by using Kubernetes Event‑driven Autoscaling (KEDA) in Container Apps

Scale apps in Azure Container Apps

Scale Containers in Azure Container Apps – Training

Kubernetes Event-driven Autoscaling (KEDA) – Azure Kubernetes Service

Deploy and manage applications to Azure Kubernetes Service (AKS) by using manifest files

Tutorial: Create an Azure Container Registry and build images for AKS

Deploy and manage applications on AKS – Training

Deploy applications to Azure Kubernetes Service

Monitor and troubleshoot solutions on AKS and Container Apps by inspecting logs, events, and end-to-end connectivity

Monitor Azure Kubernetes Service – Azure Monitor

Logging in Azure Container Apps

AKS troubleshooting – Azure Kubernetes Service

Develop AI solutions by using Azure data management services (25–30%)

Develop AI solutions by using Azure Cosmos DB for NoSQL

Connect to Azure Cosmos DB for NoSQL by using the SDK and run queries

Azure Cosmos DB overview

Quickstart: Azure Cosmos DB for NoSQL – Python SDK

Query items using the SDK – Azure Cosmos DB for NoSQL

Optimize query performance and Request Units (RUs) consumption by using indexing policies and consistency levels

Indexing policies in Azure Cosmos DB

Manage indexing policies in Azure Cosmos DB for NoSQL

Consistency levels in Azure Cosmos DB

Store and retrieve embeddings and execute vector similarity search for semantic retrieval

Vector search in Azure Cosmos DB for NoSQL

Integrated vector database in Azure Cosmos DB

Index and query vector data in .NET – Azure Cosmos DB

Implement a change feed processor to detect and handle new or updated items

Change feed processor in Azure Cosmos DB

Develop with the change feed – Azure Cosmos DB for NoSQL

Develop AI solutions by using Azure Database for PostgreSQL

Connect and query Azure Database for PostgreSQL by using SDKs

Quickstart: Connect with Python – Azure Database for PostgreSQL Flexible Server

Generative AI with Azure Database for PostgreSQL – Flexible Server

Model schemas and implement indexing strategies, including designing tables and choosing appropriate data types

Generative AI with Azure Database for PostgreSQL – Flexible Server

Generate vector embeddings with Azure OpenAI in Azure Database for PostgreSQL

Implement indexing strategies, including optimizing query latency and reducing pgvector compute overhead

Optimize performance of vector data on Azure Database for PostgreSQL deployed with pgvector

Enable and use DiskANN – Azure Database for PostgreSQL

Configure compute, memory, and storage resources to support vector workloads

Optimize performance of vector data with pgvector – Azure Database for PostgreSQL Flexible Server

Compute options in Azure Database for PostgreSQL – Flexible Server

Run vector similarity search, including storing embeddings, semantic retrieval, and implementing retrieval-augmented generation (RAG) patterns by using metadata filter

Vector search on Azure Database for PostgreSQL

Implement Vector Search with Azure Database for PostgreSQL – Training

Generative AI with Azure Database for PostgreSQL – Flexible Server

Implement connection optimization to improve throughput and minimize latency

Connection pooling with PgBouncer – Azure Database for PostgreSQL Flexible Server

Best practices for connecting to Azure Database for PostgreSQL – Flexible Server

Integrate Azure Managed Redis in AI solutions

Implement Azure Managed Redis data operations, including caching, expiration, and invalidation

Azure Managed Redis documentation

Enhance AI solutions with Azure Managed Redis – Training

Caching guidance – Azure Architecture Center

Implement vector indexing to enable similarity search

About vector embeddings and vector search in Azure Managed Redis

Implement Vector Storage in Azure Managed Redis – Training

Using Redis modules with Azure Managed Redis

Connect to and consume Azure services (20–25%)

Develop event- and message-based AI solutions

Queue and process back-end operations by using Azure Service Bus, including dead-letter queue handling, messages, topics, and subscriptions

Introduction to Azure Service Bus messaging

Service Bus dead-letter queues – Azure Service Bus

Enable dead lettering for Azure Service Bus queues and subscriptions

Advanced features in Azure Service Bus messaging

Implement event-driven workflows by using Azure Event Grid, including filters, custom events, and retries

Introduction to Azure Event Grid

Quickstart: Send custom events to an Azure function – Event Grid

Function as event handler for Azure Event Grid events

Azure Event Grid bindings for Azure Functions

Develop and implement Azure Functions

Build serverless APIs, including implementing triggers and bindings

Azure Functions triggers and bindings concepts

Azure Functions trigger and binding example

Connect to eventing and messaging services in Azure Functions

HTTP trigger for Azure Functions

Configure and deploy function apps

Configure and deploy function apps – Azure Functions

Deployment technologies in Azure Functions

Azure Functions on Azure Container Apps overview

Secure, monitor, and troubleshoot Azure solutions (20–25%)

Implement secure Azure solutions

Secure secrets by using Azure Key Vault, including rotation and retrieval

Secure your Azure Key Vault

Secure your Azure Key Vault secrets

Rotation tutorial for resources with one set of authentication credentials stored in Azure Key Vault

Rotation tutorial for resources with two sets of authentication credentials

Use Key Vault references as App Settings – Azure App Service

Store and retrieve app configuration information by using Azure App Configuration

Tutorial: Use Key Vault references in an ASP.NET Core app – Azure App Configuration

Reload secrets and certificates from Key Vault automatically – Azure App Configuration

Azure App Configuration overview

Monitor and troubleshoot Azure solutions

Trace distributed systems by using OpenTelemetry SDKs

Enable OpenTelemetry in Application Insights – Azure Monitor

Add and modify OpenTelemetry in Application Insights – Azure Monitor

Monitor Azure Functions with OpenTelemetry distributed tracing

Use OpenTelemetry with Azure Functions

Write KQL queries to analyze logs and metrics

Azure Monitor overview

Log Analytics tutorial – Azure Monitor

Kusto Query Language (KQL) overview

Get started with KQL queries – Azure Monitor

This brings us to the end of the AI-200 Developing AI Cloud Solutions on Azure Study Guide.

What do you think? Let me know in the comments section if I have missed out on anything. Also, I love to hear from you about how your preparation is going on!

In case you are preparing for other Azure certification exams, check out the Azure certification study guides for those exams.

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