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The AI-100 exam is a challenging exam that requires a strong understanding of Azure AI solutions. Candidates must have experience working with Azure services and be familiar with data storage solutions and data processing technologies. Additionally, candidates must have experience designing and implementing AI solutions using Azure services. AI-100J exam is designed to test the candidate's ability to design AI solutions that meet business requirements and can be implemented using Azure services.
Reference: https://www.microsoft.com/en-us/learning/exam-ai-100.aspx
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Microsoft AI-100 (Designing and Implementing an Azure AI Solution) Exam is a certification exam that is designed to test a candidate's practical skills in designing and implementing AI and machine learning solutions using different Azure technologies. AI-100J exam evaluates the candidate's ability to deploy AI models, automate machine learning-based workflows, and analyze data using Azure services to deliver business value. AI-100J exam requires a thorough understanding of data analysis, natural language processing, and computer vision.
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Passing the Microsoft AI-100 exam and obtaining the corresponding certification will prove to be of great help in advancing your career. After successfully completing this test, you will get loads of career proposals. It will be easier for you to get a decent job and earn a much higher salary. Here are some of the positions you can apply for:
- Customer Engineer
- AI Engineer
- AI Strategy Architect
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Microsoft AI-100日本語 Exam Syllabus Topics:
| Section | Objectives |
| Implement Computer Vision Solutions | - Image analysis and processing
- 1. Custom Vision training and deployment
- 2. Computer Vision API usage
|
| Responsible AI and Monitoring | - AI ethics and governance
- 1. Responsible AI principles
- 2. Model monitoring and evaluation
|
| Implement Natural Language Processing (NLP) | - Language understanding solutions
- 1. Intent recognition
- 2. Entity extraction
- Text analytics solutions
- 1. Key phrase extraction
- 2. Sentiment analysis
|
| Implement Knowledge Mining and Search Solutions | - Azure Cognitive Search
- 1. Skillsets and enrichment pipeline
- 2. Indexing and querying data
|
| Design AI Solutions on Azure | - Select appropriate Azure AI services
- 1. Knowledge mining solutions
- 2. Azure Cognitive Services selection
- 3. Azure Machine Learning integration
- Design conversational AI solutions
- 1. Azure Bot Service architecture
- 2. Language understanding (LUIS concepts)
|