Microsoft AI-901: Build and Test Your First Foundry Agent
An agent adds decisions and tools to a model conversation A chat completion can answer a question with the context it already receives.…
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Microsoft AI-901: Text and Speech AI in Microsoft Foundry
Text and speech are related, but they are not one workload A user speaks a complaint into a phone, the application converts the…
Read articleMicrosoft AI-901: Vision and Image Generation in Microsoft Foundry
An image can be the input, the evidence, or the output Microsoft’s AI-901 objectives distinguish interpreting visual input, creating visual outputs with generative…
Read articleMicrosoft AI-901: Content Understanding: Documents, Audio, and Video
Information extraction turns messy media into defined fields A user sends an invoice, a screenshot of a damaged parcel, a support-call recording, or…
Read articleAWS AIP-C01: GenAI Troubleshooting and Release Failure Analysis
Generative AI applications fail in ways that do not resemble ordinary deterministic software. A request may succeed at HTTP level while returning the…
Read articleAWS AIP-C01: Latency, Throughput, and Inference Caching
Production GenAI performance combines retrieval, prompt assembly, token generation, guardrails, tool calls and network latency. A faster model response alone does not prove…
Read articleAWS AIP-C01: PII, Residency, and AI Compliance Controls
A GenAI application can leak personal or regulated data through retrieval, model invocation, tool output, logs, embeddings, caches or human review. AWS AIP-C01…
Read articleAWS AIP-C01: Event-Driven GenAI and Enterprise API Integration
Enterprise generative AI rarely consists of one synchronous prompt. A production workload may combine event intake, identity federation, document extraction, retrieval, model inference,…
Read articleAWS AIP-C01: MCP Tools, Human Approval, and Agent Boundaries
An agent can propose a tool operation, but the foundation model should never be the final authority to execute it. AWS AIP-C01 includes…
Read articleAWS AIP-C01: Bedrock Converse, Streaming, and Retry Contracts
A production foundation-model API is not a simple function that always returns text. Amazon Bedrock models and APIs differ in supported media, tool…
Read articleAWS AIP-C01: Hybrid Retrieval, Reranking, and Query Evaluation
Vector search is only one stage in a production retrieval pipeline. AWS AIP-C01 requires developers to design retrieval that handles exact identifiers, semantic…
Read articleAWS AIP-C01: Fine-Tuning, RAG, and Model Customization Choices
A team can change model behavior through prompt design, retrieval, fine-tuning or a custom deployed model. These approaches solve different problems. AWS AIP-C01…
Read articleAWS AIP-C01: Multimodal Data Quality and Ingestion Pipelines
Foundation models are only as reliable as the documents, events, images and records given to them. AWS AIP-C01 covers ingestion and formatting as…
Read articleAWS AIP-C01: Model Selection, Routing, and Resilient Inference
Choosing a foundation model for production requires evidence about task quality, supported features, latency, geography, capacity and recovery. A public benchmark may favor…
Read articleAWS AIP-C01: Five-Domain Study Plan and Professional Readiness
AWS Certified Generative AI Developer – Professional AIP-C01 is a production engineering exam, not a trivia test about chatbots. A practical study plan…
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