Develop AI cloud solutions on Microsoft Azure Training in Global

This comprehensive course enables developers to build, deploy, and manage modern AI-powered cloud applications on Microsoft Azure. Participants gain practical experience with Azure compute platforms, containerized workloads, serverless architectures, messaging systems, and AI-focused data services.

Throughout the program, learners work with Azure Container Registry, Azure Container Apps, Azure Kubernetes Service (AKS), Azure Functions, Azure Cosmos DB, Azure Database for PostgreSQL, Azure Managed Redis, Azure Monitor, and other core Azure services to create scalable and production-ready AI solutions.

Participants should have:

• Experience with Python, .NET, JavaScript, or another programming language
• Fundamental cloud computing knowledge
• Familiarity with Docker and container technologies
• Understanding of Azure fundamentals
• Experience using Azure CLI
• Basic REST API knowledge
• Familiarity with PostgreSQL or NoSQL databases (recommended)

By the end of the course, participants will be able to:

• Manage container images using Azure Container Registry
• Deploy and operate applications on Azure App Service, Container Apps, and AKS
• Build AI data solutions using Azure Cosmos DB and Azure Database for PostgreSQL
• Implement vector search and semantic retrieval patterns
• Use Azure Managed Redis for caching, messaging, and vector workloads
• Create event-driven architectures with Azure Service Bus and Event Grid
• Develop serverless APIs using Azure Functions
• Secure applications with Azure Key Vault
• Implement observability using OpenTelemetry and Azure Monitor

Container Management with Azure Container Registry

• Registry architecture
• Repositories and artifacts
• ACR Tasks
• Image versioning and lifecycle management

Deploying Containers to Azure App Service

• Container deployment strategies
• Runtime configuration
• Application settings management
• Monitoring and troubleshooting

Azure Container Apps

• Container Apps environments
• Azure CLI and YAML deployments
• Secrets and environment variables
• Deployment validation and logging

Managing Azure Container Apps

• Revision management
• Health probes
• Troubleshooting deployments
• Resource optimization

Autoscaling with KEDA

• Event-driven scaling concepts
• KEDA triggers and scalers
• Traffic routing strategies
• Cost and performance optimization

Azure Kubernetes Service (AKS)

• Kubernetes deployments
• Service exposure and networking
• Persistent storage integration
• Monitoring and diagnostics

Azure Cosmos DB for NoSQL

• Document-based storage
• Query development
• RAG document stores
• Performance optimization

Vector Search with Azure Cosmos DB

• Embedding storage
• Similarity search queries
• Metadata filtering
• Semantic search solutions

Azure Database for PostgreSQL

• Database administration
• Schema management
• Relational data access
• AI application integration

Vector Search with PostgreSQL and pgvector

• Embedding management
• Vector indexing
• Similarity search techniques
• Retrieval-based AI architectures

Azure Managed Redis

Data Operations

• Storage and retrieval
• Caching strategies

Messaging

• Redis Pub/Sub
• Redis Streams
• Queue-based processing

Vector Workloads

• Semantic search
• Vector indexing
• High-performance retrieval

Azure Service Bus

• Queues and Topics
• Reliable messaging patterns
• AI workload integration

Azure Event Grid

• Event-driven architecture
• Event publishing and subscriptions
• Delivery and retry policies

Azure Functions

• Triggers and bindings

• Serverless APIs
• Identity and access management
• AI workflow integrations

Azure Key Vault and Azure App Configuration

• Secret management
• Certificate storage
• Centralized configuration
• Feature flag implementation

OpenTelemetry and Azure Monitor

• Distributed tracing
• Telemetry collection
• Application monitoring
• KQL queries
• Dashboards and Workbooks
• Alerting and anomaly detection