| Plan and manage an Azure AI solution |
25-30% |
Choose the appropriate Foundry services for generative AI and agents
- Choose an appropriate model for each task, including large language models (LLMs), small language models, multimodal models, and Foundry Tools
- Choose the appropriate Foundry services for generative tasks, grounding, vector search, agent workflows, or multimodal processing
- Choose an appropriate method for retrieval and indexing
- Choose appropriate memory, tool, and knowledge integration services for agent solutions
Set up AI solutions in Foundry
- Design Azure infrastructure for AI apps and agent-based solutions
- Choose appropriate deployment options
- Configure model and agent deployments
- Integrate Foundry projects with continuous integration and continuous deployment (CI/CD) pipelines
Manage, monitor, and secure AI systems
- Manage quotas, scaling, rate limits, and cost footprints for model and agent workloads
- Monitor model performance, drift, safety events, and grounding quality
- Monitor data ingestion quality, search index health, and relevance performance
- Configure security, including managed identity, private networking, keyless credentials, and role policies
Implement responsible AI across generative AI and agentic systems
- Configure safety filters, guardrails, risk detection, and content moderation
- Apply responsible AI instrumentation, including evaluators, safety evaluations, and explanation tooling
- Implement auditing through trace logging, provenance metadata, and approval workflows
- Govern agent behavior with oversight modes, constraints, and tool-access controls
|
| Implement generative AI and agentic solutions |
30-35% |
Build generative applications by using Foundry
- Deploy and consume LLMs, small models, code models, and multimodal models
- Implement retrieval-augmented generation (RAG) in an application
- Design workflows, tool-augmented flows, and multistep reasoning pipelines
- Evaluate models and apps, including detecting fabrications, relevance, quality, and safety
- Integrate generative workflows into applications by using Foundry SDKs and connectors
- Configure an application to connect to a Foundry project
Build agents by using Foundry
- Define agent roles, goals, conversation-tracking approach, and tool schemas
- Build agents that integrate retrieval, function-calling, and conversation memory
- Integrate agent tools, including APIs, knowledge stores, search, content understanding, and custom functions
- Implement orchestrated multi-agent solutions
- Build autonomous or semiautonomous workflows with safeguards and approval flow controls
- Integrate monitoring into deployed agents, evaluate agent behavior, and perform error analysis
Optimize and operationalize generative AI systems
- Tune generation behavior, such as prompt engineering and adjusting model parameters
- Implement model reflection, chain-of-thought evaluations, and self-critique loops
- Set up observability by implementing tracing, token analytics, safety signals, and latency breakdowns
- Orchestrate multiple models, flows, or hybrid LLM and rules engines
|
| Implement computer vision solutions |
10-15% |
Design and implement image- and video-generation solutions
- Implement a solution that generates images from text prompts and reference media
- Implement a solution that generates videos from text prompts and reference media
- Configure image-editing workflows, including inpainting, mask based edits, and prompt driven modifications
- Implement workflows to edit generated videos
- Select and apply appropriate generation and editing controls provided by the platform
Design and implement multimodal understanding workflows
- Build a solution that analyzes visual context by using multimodal models
- Configure apps to produce concise or detailed captions for single or multiple images
- Implement a solution that enables question answering grounded in visual evidence
- Configure generation of alt text and extended image descriptions aligned to accessibility guidelines
- Implement visual understanding by configuring Azure Content Understanding in Foundry Tools to extract visual characteristics
- Implement video analysis workflows to process and interpret video segments
- Configure single task and pro mode Content Understanding pipelines
- Implement solutions that identify objects, components, or regions within images or video
Implement responsible AI for multimodal content
- Implement filters to classify unsafe or disallowed visual content
- Detect and mitigate indirect prompt injection by using embedded text in images
- Enforce visual policy rules, such as applying watermarks, flagging prohibited symbols, upholding brand usage requirements, and detecting potentially inappropriate content
|
| Implement text analysis solutions |
10-15% |
Apply language model text analysis
- Implement solutions to extract entities, topics, summaries, and structured JSON outputs by using generative prompting and Foundry Tools
- Configure detection of sentiment, tone, safety issues, and sensitive content
- Build solutions that translate text by using Azure Translator in Foundry Tools or LLM powered translation flows
- Customize language model outputs for domain tasks, such as compliance summarization and domain extraction
Implement speech solutions
- Implement workflows to convert speech to text and text to speech for agentic interactions
- Integrate speech as an agent modality, including custom speech models
- Enable multimodal reasoning from audio inputs
- Translate speech into other languages by using language models and Foundry Tools
|
| Implement information extraction solutions |
10-15% |
Build retrieval and grounding pipelines
- Ingest and index content, such as documents, images, audio, and video
- Configure semantic search, hybrid search, and vector search for grounding
- Implement enrichment by using custom or built-in skills for text, images, and layout
- Configure RAG ingestion flow, including documents and using optical character recognition (OCR)
- Connect retrieval pipelines directly to workflows and agent tools
|
| Official Information |
|
https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-103 |
