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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.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
Target Audience
The Microsoft AI-900 exam is designed for those individuals who have little to no experience in the world of IT. It is aimed at the students with both non-technical and technical backgrounds. They have basic programming experience and knowledge. However, they are not required to have software engineering or data science experience.
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Career Opportunities
The individuals can pursue a lot of career opportunities with a Microsoft certificate. The Microsoft Certified: Azure AI Fundamentals certification is not an exception. Although it is a foundational-level path, the certificate holders can start their careers on a good footing. Some of the job titles that these entry-level professionals can apply for include an Azure Data Scientist, an Azure AI Engineer, an Azure Administrator, an Azure Developer, an Azure Solution Architect, and an Azure DevOps Engineer. For these positions, the applicants can expect to earn an average of $80,000 per annum.
Microsoft AI-900 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Features of computer vision workloads on Azure | 15-20% | - Computer vision solutions
|
| Features of natural language processing (NLP) workloads on Azure | 30-35% | - Text analytics and language understanding
|
| Describe AI workloads and considerations | 20-25% | - Fundamentals of artificial intelligence concepts
|
| Fundamentals of machine learning on Azure | 25-30% | - Core machine learning concepts
|



