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Speaking of the exam details, the test will contain from 40 to 60 questions of various types which you need to complete within 100 or 120 minutes (depends on the inclusion of labs). To pass the exam you need to schedule the test on the PearsonVUE platform, pay an exam fee which is currently $165, and score at least 700 points or more out of 1000. And, of course, the knowledge of exam topics is a must.

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Languages: English, Japanese, Chinese (Simplified), Korean

Retirement date: none

This exam measures your ability to accomplish the following technical tasks: plan and manage an Azure Cognitive Services solutions; implement Computer Vision solutions; implement natural language processing solutions; implement knowledge mining solutions; and implement conversational AI solutions.

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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

  • England - 90,532 POUND
  • Europe - 90,547 EURO
  • India - 20,00,327 INR
  • United State - 120,000 USD

The benefit of obtaining the AI-102: Designing and Implementing an Azure AI Solution Exam Certification

  • AI-102 credential delivers higher earning potential and increased promotion opportunities because it shows a good understanding of designing and implementing an Azure AI Solution
  • AI-102 certified candidates will be confident and stand different from others as their skills are more trained than non-certified professionals.
  • This certification will be judging your skills and knowledge on your understanding Designing and Implementing an Azure AI Solution concepts & Understanding of how to operate on Planning and Administering Designing and Implementing an Azure AI Solution .
  • This certification credential will give you edge over other counterparts. Apart from knowledge from AI-102: Designing and Implementing an Azure AI Solution Exam.
  • AI-102 Exam provide proven knowledge to use the tools to complete the task efficiently and cost effectively than the other non-certified professionals lack in doing so.
  • AI-102 Certification provides practical experience to candidates from all the aspects to be a proficient worker in the organization.
  • AI-102 certification has more useful and relevant networks that help them in setting career goals for themselves. AI-102 networks provide them with the correct career guidance than non certified generally are unable to get.
  • AI-102 Certifications provide opportunities to get a job easily in which they are interested in instead of wasting years and ending without getting any experience.
  • AI-102 Certification is distinguished among competitors. AI-102 certification can give them an edge at that time easily when candidates appear for employment interview, employers are very fascinated to note one thing that differentiates the individual from all other candidates.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102

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Microsoft AI-102 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Plan and manage an Azure AI solution20-25%- Plan solutions aligned with responsible AI principles
- Select suitable AI models
- Select appropriate Microsoft Foundry Services
- Create and configure Azure AI resources
- Monitor, optimize, and secure AI solutions
- Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining
Topic 2: Implement natural language processing solutions15-20%- Build conversational AI and chatbots
- Perform text analysis, sentiment detection, and language detection
- Customize and deploy NLP models
- Implement translation and summarization
Topic 3: Implement an agentic solution5-10%- Build agents with Microsoft Foundry Agent Service
- Develop multi-agent workflows and orchestration
- Understand agent use cases and types
- Test, deploy, and optimize agents
Topic 4: Implement computer vision solutions10-15%- Process and index video content
- Analyze images and detect objects/features
- Integrate vision capabilities into applications
- Extract text and handwriting from images
- Build and deploy custom vision models
Topic 5: Implement generative AI solutions15-20%- Orchestrate multiple models and containers
- Apply prompt engineering and fine-tuning
- Deploy and manage generative models
- Integrate Azure OpenAI and other generative models
- Implement model monitoring and feedback
Topic 6: Implement knowledge mining and information extraction solutions15-20%- Extract entities, relationships, and key phrases
- Build knowledge bases and search indexes
- Ingest and process structured/unstructured data
- Implement intelligent search and retrieval
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