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

  • AI-102 Certification provides practical experience to candidates from all the aspects to be a proficient worker in the organization.
  • AI-102 certified candidates will be confident and stand different from others as their skills are more trained than non-certified professionals.
  • 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 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.
  • This certification credential will give you edge over other counterparts. Apart from knowledge from AI-102: Designing and Implementing an Azure AI Solution Exam.
  • 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 .
  • 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 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.
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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102

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Topics of AI-102: Designing and Implementing an Azure AI Solution Exam

Candidates should apprehend the examination topics before they begin of preparation. because it'll extremely facilitate them in touch the core. Our AI-102 exam dumps will include the following topics:

1. Analyze solution requirements (25-30%)

Recommend Cognitive Services APIs to meet business requirements

  • Select the appropriate data processing technologies
  • Identify automation requirements
  • Select the processing architecture for a solution
  • Identify components and technologies required to connect service endpoints
  • Select the appropriate AI models and services

Map security requirements to tools, technologies, and processes

  • Identify auditing requirements
  • Identify processes and regulations needed to conform with data privacy, protection, and regulatory requirements
  • Identify appropriate tools for a solution
  • Identify which users and groups have access to information and interfaces

Select the software, services, and storage required to support a solution

  • Identify appropriate services and tools for a solution
  • Identify storage required to store logging, bot state data, and Cognitive Services output
  • Identify integration points with other Microsoft services

2. Design AI solutions (40-45%)

Design solutions that include one or more pipelines

  • Design pipelines that use AI apps
  • Design a strategy for ingest and egress data
  • Design pipelines that call Azure Machine Learning models
  • Define an AI application workflow process
  • Select an AI solution that meet cost constraints
  • Design the integration point between multiple workflows and pipelines

Design solutions that uses Cognitive Services

  • Design solutions that use vision, speech, language, knowledge, search, and anomaly detection APIs

Design solutions that implement the Bot Framework

  • Design bots that integrate with channels
  • Integrate bots and AI solutions
  • Design bot services that use Language Understanding (LUIS)
  • Integrate bots with Azure app services and Azure Application Insights

Design the compute infrastructure to support a solution

  • Identify whether to create a GPU, FPGA, or CPU-based solution
  • Select a compute solution that meets cost constraints
  • Identify whether to use a cloud-based, on-premises, or hybrid compute infrastructure

Design for data governance, compliance, integrity, and security

  • Design strategies to ensure that the solution meets data privacy regulations and industry standards
  • Design a content moderation strategy for data usage within an AI solution
  • Ensure appropriate governance of data
  • Ensure that data adheres to compliance requirements defined by your organization
  • Define how users and applications will authenticate to AI services

3. Implement and monitor AI solutions (25-30%)

Implement an AI workflow

  • Manage the flow of data through the solution components
  • Develop AI pipelines
  • Develop streaming solutions
  • Create solution endpoints
  • Implement data logging processes
  • Define and construct interfaces for custom AI services

Integrate AI services with solution components

  • Implement Azure Search in a solution
  • Configure prerequisite components and input datasets to allow the consumption of Cognitive Services APIs
  • Configure prerequisite components to allow connectivity to the Bot Framework
  • Configure integration with Cognitive Services

Monitor and evaluate the AI environment

  • Maintain an AI solution for continuous improvement
  • Recommend changes to an AI solution based on performance data
  • Identify the differences between expected and actual workflow throughput
  • Monitor AI components for availability
  • Identify the differences between KPIs, reported metrics, and root causes of the differences

Skills measured

  • Implement knowledge mining solutions (15-20%)
  • Implement Computer Vision solutions (20-25%)
  • Implement conversational AI solutions (15-20%)
  • Plan and manage an Azure Cognitive Services solution (15-20%)
  • Implement natural language processing solutions (20-25%)

Microsoft AI-102日本語 Exam Syllabus Topics:

SectionObjectives
Implement Generative AI Solutions- Implement Azure OpenAI Service solutions
- Integrate prompt engineering techniques
- Build retrieval-augmented generation (RAG) solutions
Implement Natural Language Processing Solutions- Translate and interpret language using Azure AI services
- Analyze text using Azure AI Language
- Implement question answering and conversational AI
Plan and Manage an Azure AI Solution- Plan solution requirements and architecture
- Select appropriate Azure AI services
- Manage security, compliance, and responsible AI
Implement Computer Vision Solutions- Analyze images and videos using Azure AI Vision
- Implement custom vision models
- Extract information using OCR and form recognition
Implement Knowledge Mining and Document Intelligence- Build Azure AI Search solutions
- Enrich and index data for search scenarios
- Implement document intelligence solutions

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