What are the main skill areas assessed in the AI-900 exam?

[BoultLT]

I am planning to start preparing for the AI-900 exam, and I want to make sure I focus on the right areas from the beginning. Understanding the main skill areas assessed in the exam will help me structure my study plan more effectively, so I’m asking.

[pankajnamekar25 · Accepted solution]

Hello @BoultLT 

here is details breakup

1 Describe AI workloads and considerations (15–20%)

Identify common AI workloads (e.g., computer vision, NLP, ML).

Describe guiding principles for responsible AI (fairness, reliability, privacy, inclusiveness, transparency, accountability).

 2 Describe fundamental principles of machine learning on Azure (30–35%)

Identify types of machine learning (supervised, unsupervised, reinforcement learning).

Describe core ML concepts (features, labels, training, evaluation, etc.).

Identify Azure ML tools and services (Azure Machine Learning, Designer, AutoML, etc.).

3 Describe features of computer vision workloads on Azure (15–20%)

identify common computer vision tasks (object detection, classification, OCR).

Describe Azure tools for computer vision (Computer Vision, Custom Vision, Face API).

 4 Describe features of Natural Language Processing (NLP) workloads on Azure (15–20%)

Identify common NLP scenarios (sentiment analysis, translation, question answering).

Describe Azure NLP services (Text Analytics, Language Understanding - LUIS, Translator).

5 Describe features of conversational AI workloads on Azure (15–20%)

Identify use cases for conversational AI.

Describe the Azure Bot Service and its integration with other tools (like QnA Maker, LUIS, etc.).

Thanks,
 Pankaj Namekar | LinkedIn

If this solution helps, please accept it and give a kudos (Like), it would be greatly appreciated.

[BoultLT]

Thanks

[bhanu_gautam · Accepted solution]

@BoultLT Describe Artificial Intelligence workloads and considerations
Describe fundamental principles of machine learning on Azure
Describe features of computer vision workloads on Azure
Describe features of Natural Language Processing (NLP) workloads on Azure
Describe features of generative AI workloads on Azure

https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-fundamentals/?practice-assessm... Go to link for more

[pankajnamekar25 · Accepted solution]

Hello @BoultLT 

here is details breakup

1 Describe AI workloads and considerations (15–20%)

Identify common AI workloads (e.g., computer vision, NLP, ML).

Describe guiding principles for responsible AI (fairness, reliability, privacy, inclusiveness, transparency, accountability).

 2 Describe fundamental principles of machine learning on Azure (30–35%)

Identify types of machine learning (supervised, unsupervised, reinforcement learning).

Describe core ML concepts (features, labels, training, evaluation, etc.).

Identify Azure ML tools and services (Azure Machine Learning, Designer, AutoML, etc.).

3 Describe features of computer vision workloads on Azure (15–20%)

identify common computer vision tasks (object detection, classification, OCR).

Describe Azure tools for computer vision (Computer Vision, Custom Vision, Face API).

 4 Describe features of Natural Language Processing (NLP) workloads on Azure (15–20%)

Identify common NLP scenarios (sentiment analysis, translation, question answering).

Describe Azure NLP services (Text Analytics, Language Understanding - LUIS, Translator).

5 Describe features of conversational AI workloads on Azure (15–20%)

Identify use cases for conversational AI.

Describe the Azure Bot Service and its integration with other tools (like QnA Maker, LUIS, etc.).

Thanks,
 Pankaj Namekar | LinkedIn

If this solution helps, please accept it and give a kudos (Like), it would be greatly appreciated.