Exam Objectives
This exam is intended for individuals who want to start working with AI solutions built on Azure. It is suitable for learners from technical backgrounds, including aspiring junior developers who are starting to incorporate AI capabilities into applications. As a candidate for this certification, you should have familiarity with the self-paced or instructor-led learning material.
Candidates for this exam should have foundational knowledge of core cloud concepts, using Microsoft Foundry to deploy models and implement single-agent solutions, recognizing how client applications are put together and how AI models and services are consumed within those solutions, and understanding Python code examples that call AI models and services.
Skills at a glance
- Identify AI concepts and responsibilities (40–45%)
- Implement AI solutions by using Microsoft Foundry (55–60%)
Identify AI concepts and capabilities (40–45%)
Describe principles of responsible AI
- Describe considerations for fairness in an AI solution
- Describe considerations for reliability and safety in an AI solution
- Describe considerations for privacy and security in an AI solution
- Describe considerations for inclusiveness in an AI solution
- Describe considerations for transparency in an AI solution
- Describe considerations for accountability in an AI solution
Identify AI model components and configurations
- Describe how generative AI models work
- Identify an appropriate AI model, based on capabilities
- Identify appropriate model deployment options and configuration parameters
Identify AI workloads
- Identify scenarios for common AI workloads, including generative and agentic AI, text analysis, speech, computer vision, and information extraction
- Describe common text analysis techniques, including keyword extraction, entity detection, sentiment analysis, and summarization
- Identify features and capabilities of speech recognition and speech synthesis
- Identify features and capabilities of computer vision and image-generation models
- Identify techniques to extract information from text, images, audio, and videos
Implement AI solutions by using Microsoft Foundry (55–60%)
Implement generative AI apps and agents by using Foundry
- Create effective system and user prompts for generative AI models
- Deploy a model and interact with it in the Foundry portal
- Create a lightweight chat client application by using the Foundry SDK
- Create and test a single-agent solution in the Foundry portal
- Create a lightweight client application for an agent
Implement AI solutions for text and speech by using Foundry
- Build a lightweight application that includes text analysis
- Respond to spoken prompts by using a deployed multimodal model
- Build a lightweight application by using Azure Speech in Foundry Tools
Implement AI solutions with computer vision and image-generation capabilities by using Foundry
- Interpret visual input in prompts by using a deployed multimodal model
- Create new visual outputs by using generative models
- Build a lightweight application that includes vision capabilities
Implement AI solutions for information extraction by using Foundry
- Extract information from documents and forms by using Azure Content Understanding in Foundry Tools
- Extract information from images by using Content Understanding
- Extract information from audio and video by using Content Understanding
- Build a lightweight application with information extraction capabilities by using Content Understanding
MCF Overview
The pathway to AI, Data Science, and Cloud Computing.
The Microsoft Certified Fundamentals exams are the pathway to fully understanding what cloud computing is, what options are available from Microsoft, and which options make sense for businesses to invest in. This set of exams is for students who are exploring a career in artificial intelligence, data science, and cloud computing. With the usage of big data and artificial intelligence on the rise, the demand for data scientists is not being met—and the gap is widening.
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