Microsoft AI-200 Certification Study
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Microsoft AI-200 Certification Study English

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Start hereUnited States18 min read

AI-200 Exam: Audience, Skills, and the AZ-204 Replacement

Who the exam is for, expected experience, current domains, the transition from AZ-204, and why AI-103—not AI-200—replaced AI-102.

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Chapter 1United States70 min read

Azure Container Registry: ACR Tasks, Image Tags, and Versioning

Organize OCI artifacts, build in Azure, automate triggers, pin digests, version releases, lock production images, and manage registry retention.

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Chapter 2United States75 min read

Deploy Containers to Azure App Service: Runtime, Settings, and Diagnostics

Deploy private images with managed identity, configure ports, storage, health and slots, protect secrets, and troubleshoot with Kudu and Azure Monitor.

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Chapter 3United States70 min read

Azure Container Apps: Environments, YAML, Secrets, Private Images, and Logs

Design environment boundaries, deploy with CLI and YAML, externalize configuration, pull private images with identity, and verify revisions, replicas, and logs.

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Chapter 4United States75 min read

Operate Container Apps: Revisions, Health Probes, Logs, and Scaling

Release immutable images, control revisions and traffic, use lifecycle actions, diagnose with logs, tune health probes, and balance resources with KEDA scaling.

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Chapter 5United States90 min read

Autoscale Container Apps: KEDA, Compute Profiles, Revisions, and Traffic

Configure HTTP, TCP, resource, queue, stream, schedule, and custom metric triggers; right-size compute and deliver with revision-aware traffic control.

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Chapter 6United States80 min read

Deploy AI APIs to AKS: Kubernetes Manifests, Services, and Diagnostics

Create Deployments and Services, set replicas and resources, publish with LoadBalancer, apply with kubectl, verify endpoints, and troubleshoot failures.

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Chapter 7United States85 min read

Configure AKS Apps: ConfigMaps, Secrets, Key Vault, PVs, and PVCs

Externalize settings, protect credentials, integrate Key Vault, dynamically provision durable storage, choose CSI classes, and prove data survives Pod replacement.

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Chapter 8United States85 min read

Monitor and Troubleshoot AKS: Logs, Metrics, Pods, and Services

Correlate Azure Monitor and kubectl evidence, diagnose Pod states, inspect EndpointSlices, validate Services, and test ingress and load-balancer paths.

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Chapter 9United States95 min read

Azure Cosmos DB for NoSQL: Partitions, SDK, CRUD, Queries, and RAG

Model resources and partition keys, provision RU/s, authenticate with Microsoft Entra ID, implement Python SDK operations, optimize SQL queries, and build a RAG store.

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Chapter 10United States105 min read

Cosmos DB Vector Search: Embeddings, DiskANN, Hybrid Search, and Change Feed

Store and index embeddings, query with VectorDistance, combine metadata and RRF hybrid ranking, and refresh vectors through Azure Functions and the change feed.

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Chapter 11United States115 min read

Cosmos DB Indexing Performance: Composite and Vector Indexes, RU, and Consistency

Design selective range, composite, tuple, and vector indexes, measure query efficiency and RU cost, and select consistency guarantees for AI search.

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Chapter 12United States125 min read

Azure Database for PostgreSQL: Secure Connections, SQL, JSONB, and psycopg

Choose compute and recovery options, connect with Microsoft Entra ID and TLS, design schemas and queries, and build persistent AI agent memory with Python.

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Chapter 13United States130 min read

PostgreSQL Vector Search: pgvector, HNSW, IVFFlat, and RAG

Store embeddings, tune ANN indexes, maintain evolving vectors, combine semantic and lexical retrieval, and ground RAG answers with citations.

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Chapter 14United States125 min read

PostgreSQL Vector Performance: Tuning, Indexes, Scaling, and Pooling

Tune memory and planning, choose and maintain ANN indexes, optimize metadata filters, scale reads, cache results, and pool connections safely.

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Chapter 15United States105 min read

Azure Managed Redis: Client Libraries, Caching, and Data Operations

Design cache-aside, content and session caching, select tiers and cluster-aware clients, connect with Microsoft Entra ID, and implement TTL and invalidation.

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Chapter 16United States110 min read

Azure Managed Redis: Pub/Sub, Streams, Events, and Task Queues

Broadcast real-time events, coordinate durable work with consumer groups, recover pending deliveries, scale workers, and combine Pub/Sub with Streams.

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Chapter 17United States120 min read

Azure Managed Redis Vector Search: HNSW, FLAT, Hash, and JSON

Index embeddings, run KNN and range queries, filter metadata, choose metrics and numeric types, tune HNSW, and model vectors in Hash or JSON.

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Chapter 18United States125 min read

Azure Service Bus: Queues, Topics, Subscriptions, and Reliable AI Messaging

Decouple inference with load leveling, competing consumers, filtered fan-out, structured messages, Peek-Lock, idempotency, lock renewal, and DLQ recovery.

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Chapter 19United States125 min read

Azure Event Grid: CloudEvents, Filters, Retries, and Custom AI Events

Route system and custom events with CloudEvents, filtered subscriptions, push or pull delivery, retries, dead-lettering, batching, monitoring, and secure publishing.

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Chapter 20United States130 min read

Azure Functions for AI: Hosting, Scaling, Triggers, Bindings, Security, and MCP

Choose Flex Consumption or Premium, build HTTP and Service Bus flows, develop locally, secure configuration and identity, and expose MCP tools.

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Chapter 21United States125 min read

Azure Key Vault: Secrets, SDK Access, Rotation, and Caching

Choose secrets, keys, or certificates, authorize with RBAC and managed identity, use SecretClient, rotate versions without downtime, and cache safely.

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Chapter 22United States120 min read

Azure App Configuration: Python, Labels, Feature Flags, and Key Vault References

Load and compose settings with the Python provider, refresh through a sentinel, evaluate feature flags, resolve Key Vault references, and classify configuration safely.

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Chapter 23United States125 min read

OpenTelemetry and Azure Monitor: Traces, Spans, Application Insights, and KQL

Instrument distributed AI services, propagate W3C context, control sampling, export resilient telemetry, and diagnose RAG latency with maps, transactions, and KQL.

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Chapter 24United States120 min read

KQL and Azure Monitor: Logs, Dashboards, Workbooks, and Alerts

Query and correlate Application Insights telemetry, analyze tail latency, build operational dashboards and interactive Workbooks, and configure actionable alerts.

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