Video Tutorial AI-200 Azure AI Cloud Developer Associate (1 Viewer)

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Free Download AI-200 Azure AI Cloud Developer Associate
Published 8/2026
Created by Christopher Nett | 150.000+ Enrollments
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 90 Lectures ( 8h 29m ) | Size: 2.8 GB​

Pass AI-200 | Elevate your career
What you'll learn

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Implement containerized solutions
Implement Azure App Service Web Apps
Implement Azure Functions
Develop solutions that use Azure Cosmos DB
Develop solutions that use Azure Blob Storage
Implement user authentication and authorization
Implement secure Azure solutions
Implement caching for solutions
Troubleshoot solutions by using Application Insights
Implement API Management
Develop event-based solutions
Develop message-based solutions
Requirements

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Basic IT Knowledge
Willingness to learn cool stuff!
Description

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This course contains the use of artificial intelligence.
AI-200, is a meticulously structured Udemy course aimed at IT professionals seeking to pass the AI-200 exam. This course systematically walks you through the initial setup to advanced implementation with real-world applications.
By passing AI-200, you're gaining proficiency in the highly recognized Microsoft Azure ecosystem.
Develop containerized solutions on Azure (20-25%)
Implement container application hosting
Build, store, version, and manage container images by using Azure Container Registry
Build and run images by using Azure Container Registry Tasks
Deploy containers to Azure App Service, including configuring App Service to supply environment variables and secrets
Implement container-orchestrated solutions
Deploy applications to Azure Container Apps, including environment configuration and revision management
Implement event-driven scaling by using Kubernetes Event‑driven Autoscaling (KEDA) in Container Apps
Deploy and manage applications to Azure Kubernetes Service (AKS) by using manifest files
Monitor and troubleshoot solutions on AKS and Container Apps by inspecting logs, events, and end-to-end connectivity
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
Optimize query performance and Request Units (RUs) consumption by using indexing policies and consistency levels
Store and retrieve embeddings and execute vector similarity search for semantic retrieval
Implement a change feed processor to detect and handle new or updated items
Develop AI solutions by using Azure Database for PostgreSQL
Connect and query Azure Database for PostgreSQL by using SDKs
Model schemas and implement indexing strategies, including designing tables and choosing appropriate data types
Implement indexing strategies, including optimizing query latency and reducing pgvector compute overhead
Configure compute, memory, and storage resources to support vector workloads
Run vector similarity search, including storing embeddings, semantic retrieval, and implementing retrieval-augmented generation (RAG) patterns by using metadata filter
Implement connection optimization to improve throughput and minimize latency
Integrate Azure Managed Redis in AI solutions
Implement Azure Managed Redis data operations, including caching, expiration, and invalidation
Implement vector indexing to enable similarity search
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
Implement event-driven workflows by using Azure Event Grid, including filters, custom events, and retries
Develop and implement Azure Functions
Build serverless APIs, including implementing triggers and bindings
Configure and deploy function apps
Secure, monitor, and troubleshoot Azure solutions (20-25%)
Implement secure Azure solutions
Secure secrets by using Azure Key Vault, including rotation and retrieval
Store and retrieve app configuration information by using Azure App Configuration
Monitor and troubleshoot Azure solutions
Trace distributed systems by using OpenTelemetry SDKs
Write KQL queries to analyze logs and metrics
This course contains promotional materials.
Who this course is for

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Developer
Cloud Engineer
Cloud Architect
IT Administrator
IT Manager
Identity Architect
Homepage

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https://www.udemy.com/course/ai-200-azure-ai-cloud-developer-associate-m

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