Description
Master the architecture, deployment, and optimization of enterprise-grade AI solutions. This intensive, 5-day boot camp is engineered specifically for backend developers, DevOps professionals, and software engineers tasked with building the high-performance infrastructure that drives modern AI workloads.
Through hands-on labs and expert instruction, you will learn to implement robust Azure compute and containerization patterns, deploy serverless APIs using Azure Functions, and architect resilient, event-driven messaging pipelines. Youโll also gain deep expertise in managing the underlying data layer for AI applications, including designing, scaling, and querying high-velocity databases using Cosmos DB for NoSQL and Azure Database for PostgreSQL.
The Microsoft Certified Develop AI Cloud Solutions on Azure Associate boot camp is taught using Microsoft Official Courseware
AI-200T00 – Develop AI Cloud Solutions on Azure
Everything You Need to Succeed – What’s Included
Microsoft Certified Trainer (MCT) Instructor Led Live Training
Microsoft Official Course (AI-200)
Microsoft Official Exam Voucher (AI-200)
1 Retake Voucher (if needed)
Microsoft Hands on Labs
Microsoft Vetted Practice Exam Resources
Onsite & Online Pearson Vue Test Center
Skills Gained:
Implement container application hosting on Azure
Deploy and manage apps on Azure Container Apps
Deploy and monitor applications on Azure Kubernetes Service
Develop AI solutions with Azure Cosmos DB for NoSQL
Develop AI solutions with Azure Database for PostgreSQL
Enhance AI solutions with Azure Managed Redis
Integrate backend services for AI solutions
Manage application secrets and configuration for AI solutions
Observe and troubleshoot apps on Azure
Topics Covered in this Official Boot Camp:
Store and manage containers in Azure Container Registry
Registries, repositories, and artifacts
Build and run images with ACR Tasks
Tag and version images
Deploy containers to Azure App Service
Deploy containers to Azure App Service
Configure container runtime behavior
Configure application settings
Observe and troubleshoot containerized apps
Deploy containers to Azure Container Apps
Explore Container Apps environments
Deploy a container app using the Azure CLI and YAML
Configure runtime settings with environment variables and secrets
Configure image pull authentication for private registries
Verify deployments with logs and status
Manage containers in Azure Container Apps
Update images and manage revisions safely
Manage the container app lifecycle
Monitor logs and troubleshoot issues
Configure health probes and troubleshoot failures
Optimize container resources and scaling
Scale containers in Azure Container Apps
Configure scale rules
Implement event-driven scaling with KEDA
Apply KEDA scalers for custom workloads
Select compute resources for performance and cost
Choose and apply revision modes
Deploy applications to Azure Kubernetes Service
Create Kubernetes deployment manifests
Expose applications in Azure Kubernetes Services
Deploy applications to Azure Kubernetes Services
Configure applications on Azure Kubernetes Service
Define ConfigMaps for application settings
Implement secrets for sensitive data
Attach persistent storage to an app
Monitor and troubleshoot applications on Azure Kubernetes Service
Monitor application logs and metrics
Troubleshoot pods and services
Verify service connectivity and endpoints
Build queries for Azure Cosmos DB for NoSQL
Explore Azure Cosmos DB for NoSQL
Implement the Azure Cosmos DB for NoSQL SDK
Query Azure Cosmos DB for NoSQL
Implement vector search on Azure Cosmos DB for NoSQL
Store and retrieve embeddings in Azure Cosmos DB
Execute vector similarity queries for semantic search
Combine vector similarity results with metadata filtering
Use the change feed to trigger embedding refresh
Optimize query performance for Azure Cosmos DB for NoSQL
Understand indexes in Azure Cosmos DB
Configure range and composite indexes
Tune vector indexes for embedding workloads
Reduce RU costs with strategic indexing
Choose consistency levels for optimal performance
Build and query with Azure Database for PostgreSQL
Explore Azure Database for PostgreSQL
Connect to PostgreSQL
Create and manage schemas
Query data
Integrate SDKs and applications
Implement vector search with Azure Database for PostgreSQL
Store and query embeddings with pgvector
Perform fast vector similarity search
Manage index lifecycle and embedding updates
Run vector similarity search for semantic retrieval
Implement retrieval patterns for RAG pipelines
Optimize vector search in Azure Database for PostgreSQL
Tune PostgreSQL for pgvector
Choose and configure vector indexes
Optimize data layout
Scale for high-volume workloads
Connection optimization
Implement data operations in Azure Managed Redis
Explore Azure Managed Redis
Client libraries and development best practices
Implement data operations
Implement event messaging with Azure Managed Redis
Publish and subscribe to events with Redis pub/sub
Implement task queues with Redis Streams
Choose between broadcast and coordinated distribution
Implement vector storage in Azure Managed Redis
Index and query vector data
Choose vector types and indexing strategies
Optimize Redis data structures for vector storage
Queue and process AI operations with Azure Service Bus
Explore Azure Service Bus concepts and messaging in AI architectures
Choose between queues and topics with subscriptions
Structure messages for AI workloads
Process messages reliably
Develop event-driven AI workflows with Azure Event Grid
Understand Azure Event Grid concepts and event-driven patterns for AI solutions
Work with event schemas and properties
Configure delivery and retry policies for reliable event processing
Publish custom events from AI applications
Build serverless AI backends with Azure Functions
Understand Azure Functions hosting and scaling for AI workloads
Set up the local development environment for Functions
Create triggers and bindings for AI integration patterns
Manage secrets and configuration in Functions
Configure identity and access for Functions
Manage application secrets with Azure Key Vault
Store and organize secrets, keys, and certificates
Retrieve secrets using Azure SDK client libraries
Handle secret versioning and rotation
Implement caching strategies to reduce Key Vault calls
Manage application settings with Azure App Configuration
Connect to App Configuration from application code
Organize settings with labels and feature flags
Reference Key Vault secrets from App Configuration
Decide what to store in App Configuration vs Key Vault
Instrument an app with OpenTelemetry
Explore OpenTelemetry and its role in observability
Add the OpenTelemetry SDK to an application
Configure spans and traces
Export telemetry to Azure Monitor
Debug distributed flows with trace data
Analyze app telemetry with logs and metrics
Write basic KQL queries
Explore logs for errors and performance
Build dashboards for app telemetry
Create workbooks for interactive analysis
Set alerts for app failures and anomalies
CAMPUS – Career Camps built out a stand alone training center (not a hotel conference room) with spacious classrooms, new desk, Herman Miller Aeron chairs & comfortable common areas. Each student has a dedicated desk with two monitors. Each classroom has a maximum of two rows – so everyone is able to be engaged without the “back row” feeling.




