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To prepare for the AI-102 certification exam, candidates need to have a strong understanding of machine learning algorithms, data analysis and visualization, and cloud computing technologies. They also need to have a deep understanding of the Azure platform and its various services, including Azure Cognitive Services, Azure Machine Learning, and Azure Databricks.
To prepare for the AI-102 certification exam, you should have a solid understanding of Azure fundamentals and AI concepts. You should also have experience in developing and implementing AI solutions using Azure services such as Azure Machine Learning, Azure Databricks, and Azure Bot Service.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
How to Register For Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution?
Exam Register Link: https://examregistration.microsoft.com/?locale=en-us&examcode=AI-102&examname=Exam%20AI-102:%20Designing%20and%20Implementing%20a%20Microsoft%20Azure%20AI%20Solution&returnToLearningUrl=https%3A%2F%2Fdocs.microsoft.com%2Flearn%2Fcertifications%2Fexams%2Fai-102
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Microsoft AI-102 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Implement natural language processing solutions | 15-20% | - Implement translation and summarization
- Build conversational AI and chatbots
- Perform text analysis, sentiment detection, and language detection
- Customize and deploy NLP models
|
| Implement generative AI solutions | 15-20% | - Deploy and manage generative models
- Implement model monitoring and feedback
- Integrate Azure OpenAI and other generative models
- Apply prompt engineering and fine-tuning
- Orchestrate multiple models and containers
|
| Implement knowledge mining and information extraction solutions | 15-20% | - Extract entities, relationships, and key phrases
- Build knowledge bases and search indexes
- Implement intelligent search and retrieval
- Ingest and process structured/unstructured data
|
| Implement an agentic solution | 5-10% | - Develop multi-agent workflows and orchestration
- Test, deploy, and optimize agents
- Build agents with Microsoft Foundry Agent Service
- Understand agent use cases and types
|
| Plan and manage an Azure AI solution | 20-25% | - Create and configure Azure AI resources
- Monitor, optimize, and secure AI solutions
- Select suitable AI models
- Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining
- Plan solutions aligned with responsible AI principles
- Select appropriate Microsoft Foundry Services
|
| Implement computer vision solutions | 10-15% | - Build and deploy custom vision models
- Extract text and handwriting from images
- Process and index video content
- Integrate vision capabilities into applications
- Analyze images and detect objects/features
|