Explain Conversational Artificial Intelligence Workloads Features on Azure (15-20%)

In the last section, you will face with the following subtopics:

• Establish Azure services for Conversational Artificial Intelligence – The potential candidates for the Microsoft AI-900 exam should have the capacity to identify the capabilities of Azure Bot Service and QnA Maker service.
• Identify the basic use cases for Conversational Artificial Intelligence (AI) – The students should be able to identify the features and usage for a range of elements. These include personal digital assistants, webchat bots, and telephone voice menus. It also covers the skills in identifying the basic features of conversational Artificial Intelligence solutions.

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Describe the Basic Principles of ML on Microsoft Azure (30-35%)

As for this area, it includes the following:

• Identify the basic ML types – This section equips the learners with the ability to identify various concepts, such as regression, clustering, and classification ML scenarios.
• Identify the major tasks in crafting an ML solution – This subject area measures the students’ competence in explaining some concepts, such as basic features of data preparation and ingestion, model management and deployment, model training & evaluation, and feature selection and engineering.
• Explain the abilities of the No-code ML with Azure ML Learning Studio – This domain equips the individuals with the knowledge of the Azure ML designer and automated ML UI.
• Describe the ML core concepts – You should be able to identify the labels and features within a dataset for ML and describe the usage of validation datasets and training in ML. The applicants also need the ability to explain the usage of ML algorithms in model training, as well as interpret and choose the model evaluation yardsticks for regression and classification.

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Skills measured

• Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)
• Describe features of conversational AI workloads on Azure (15-20%)
• Describe fundamental principles of machine learning on Azure (30-35%)
• Describe AI workloads and considerations (15-20%)
• Describe features of computer vision workloads on Azure (15-20%)

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900

Microsoft AI-900 中文 Exam Syllabus Topics: