AI-200T00-A: Develop AI cloud solutions on Azure

это комплексная программа обучения, ориентированная на разработчиков, которые создают, развертывают и масштабируют решения на базе искусственного интеллекта в облаке Microsoft. Программа полностью сфокусирована на интеграции ИИ-моделей с облачной архитектурой, базами данных и микросервисами.

Аудитория: Бэкенд-разработчики и ИИ-инженеры, работающие со стеком Azure.

Базовые навыки: Опыт программирования (Python, JavaScript или C#) от 1–2 лет, базовое понимание концепций облачных вычислений.

Day 1

Learning Path 1: Implement container application hosting on Azure

• Module 1: Store and manage containers in Azure Container Registry

• Module 2: Deploy containers to Azure App Service

Learning Path 2: Deploy and manage apps on Azure Container Apps

• Module 1: Deploy containers to Azure Container Apps

• Module 2: Manage containers in Azure Container Apps

• Module 3: Scale containers in Azure Container Apps

Day 2

Learning Path 3: Deploy and monitor apps on Azure Kubernetes Service

• Module 1: Deploy and verify apps on Azure Kubernetes Service

• Module 2: Configure apps on Azure Kubernetes Service

• Module 3: Monitor and troubleshoot apps on Azure Kubernetes Service

Learning Path 4: Develop AI solutions with Azure Cosmos DB for NoSQL

• Module 1: Build queries for Azure Cosmos DB for NoSQL

• Module 2: Implement vector search with Azure Cosmos DB for NoSQL

• Module 3: Optimize query performance for Azure Cosmos DB for NoSQL

Day 3

Learning Path 5: Develop AI solutions with Azure Database for PostgreSQL

• Module 1: Build and query with Azure Database for PostgreSQL

• Module 2: Implement vector search with Azure Database for PostgreSQL

• Module 3: Optimize performance, indexing, and scaling for Azure Database for

• PostgreSQL

Learning Path 6: Enhance AI solutions with Azure Managed Redis

• Module 1: Implement data operations in Azure Managed Redis

• Module 2: Stream and Coordinate Events in Azure Redis

• Module 3: Implement vector storage in Azure Managed Redis

Day 4

Learning Path 7: Integrate backend services for AI solutions

• Lesson 1: Queue and process AI operations with Azure Service Bus

• Lesson 2: Develop event-driven AI workflows with Azure Event Grid

• Lesson 3: Build serverless AI backends with Azure Functions

Learning Path 8: Manage application secrets and configuration for AI solutions

• Module 1: Manage app secrets with Azure Key Vault

• Module 2: Manage application settings with Azure App Configuration

Day 5

Learning Path 9: Observe and troubleshoot apps on Azure

• Module 1: Instrument an app with OpenTelemetry

• Module 2: Analyze app telemetry with logs and metrics