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AI– 200 Azure AI Cloud Developer Associate

   Author: Baturi   |   30 August 2026   |   Comments icon: 0


Free Download AI– 200 Azure AI Cloud Developer Associate

Download this premium online course featuring high-quality video training, step-by-step lessons, practical demonstrations, and expert instruction. With AI– 200 Azure AI Cloud Developer Associate, you'll gain practical knowledge through structured learning, hands-on examples, and real-world applications. This comprehensive eLearning resource is ideal for students, professionals, freelancers, and lifelong learners looking to develop valuable skills and stay current with modern industry practices at their own pace.
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


⚡ 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


❗ Basic IT Knowledge
❗ Willingness to learn cool stuff!

Description


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


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

Homepage

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


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