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AI-102: Designing and Implementing an Azure AI Solution Exam Certified Professional salary
The average salary of a AI-102: Designing and Implementing an Azure AI Solution Exam Certified Expert in
- India - 20,00,327 INR
- United State - 120,000 USD
- England - 90,532 POUND
- Europe - 90,547 EURO
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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How to book the AI-102: Designing and Implementing an Azure AI Solution Exam
These are following steps for registering the AI-102: Designing and Implementing an Azure AI Solution exam.
- Step 1: Visit to Microsoft Learning and search for AI-102: Developing Solutions for Microsoft Azure.
- Step 2: Sign up/Login to Pearson VUE account
- Step 3: Select local centre based on your country, date, time and confirm with a payment method.
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Prerequisites
Before enrolling in the process of taking the AI-102 exams, candidates should be skilled in implementing Python and C#, using APIs and SDKs based on REST to create natural language processing solutions, computer vision solutions, and knowledge mining and communicative AI solutions based on Azure. In addition, such specialists should be knowledgeable of the elements that create the Azure AI portfolio as well as the data storage options. To add more, they should be able to implement AI principles appropriately.
Microsoft AI-102日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement knowledge mining and information extraction solutions | 15-20% | - Implement intelligent search and retrieval - Extract entities, relationships, and key phrases - Ingest and process structured/unstructured data - Build knowledge bases and search indexes |
| Topic 2: Plan and manage an Azure AI solution | 20-25% | - Plan solutions aligned with responsible AI principles - Select appropriate Microsoft Foundry Services - Monitor, optimize, and secure AI solutions - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Select suitable AI models - Create and configure Azure AI resources |
| Topic 3: Implement generative AI solutions | 15-20% | - Integrate Azure OpenAI and other generative models - Apply prompt engineering and fine-tuning - Orchestrate multiple models and containers - Deploy and manage generative models - Implement model monitoring and feedback |
| Topic 4: Implement computer vision solutions | 10-15% | - Process and index video content - Extract text and handwriting from images - Integrate vision capabilities into applications - Analyze images and detect objects/features - Build and deploy custom vision models |
| Topic 5: Implement natural language processing solutions | 15-20% | - Implement translation and summarization - Customize and deploy NLP models - Perform text analysis, sentiment detection, and language detection - Build conversational AI and chatbots |
| Topic 6: Implement an agentic solution | 5-10% | - Test, deploy, and optimize agents - Build agents with Microsoft Foundry Agent Service - Develop multi-agent workflows and orchestration - Understand agent use cases and types |
