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- India - 20,00,327 INR
- England - 90,532 POUND
- United State - 120,000 USD
How much AI-102: Designing and Implementing an Azure AI Solution Exam Cost
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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 components and technologies required to connect service endpoints
- Select the appropriate AI models and services
- Select the processing architecture for a solution
- Identify automation requirements
Map security requirements to tools, technologies, and processes
- Identify auditing requirements
- Identify appropriate tools for a solution
- Identify processes and regulations needed to conform with data privacy, protection, and regulatory requirements
- Identify which users and groups have access to information and interfaces
Select the software, services, and storage required to support a solution
- Identify integration points with other Microsoft services
- Identify appropriate services and tools for a solution
- Identify storage required to store logging, bot state data, and Cognitive Services output
2. Design AI solutions (40-45%)
Design solutions that include one or more pipelines
- Design pipelines that call Azure Machine Learning models
- Select an AI solution that meet cost constraints
- Design the integration point between multiple workflows and pipelines
- Design a strategy for ingest and egress data
- Define an AI application workflow process
- Design pipelines that use AI apps
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
- Integrate bots with Azure app services and Azure Application Insights
- Design bot services that use Language Understanding (LUIS)
- Integrate bots and AI solutions
- Design bots that integrate with channels
Design the compute infrastructure to support a solution
- Select a compute solution that meets cost constraints
- Identify whether to use a cloud-based, on-premises, or hybrid compute infrastructure
- Identify whether to create a GPU, FPGA, or CPU-based solution
Design for data governance, compliance, integrity, and security
- Ensure appropriate governance of data
- Design strategies to ensure that the solution meets data privacy regulations and industry standards
- Ensure that data adheres to compliance requirements defined by your organization
- Define how users and applications will authenticate to AI services
- Design a content moderation strategy for data usage within an AI solution
3. Implement and monitor AI solutions (25-30%)
Implement an AI workflow
- Manage the flow of data through the solution components
- Create solution endpoints
- Implement data logging processes
- Define and construct interfaces for custom AI services
- Develop AI pipelines
- Develop streaming solutions
Integrate AI services with solution components
- 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
- Implement Azure Search in a solution
Monitor and evaluate the AI environment
- Identify the differences between KPIs, reported metrics, and root causes of the differences
- Recommend changes to an AI solution based on performance data
- Monitor AI components for availability
- Maintain an AI solution for continuous improvement
- Identify the differences between expected and actual workflow throughput
Schedule exam
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.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
Microsoft AI-102日本語 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Implement Knowledge Mining and Document Intelligence | - Implement document intelligence solutions - Enrich and index data for search scenarios - Build Azure AI Search solutions |
| Topic 2: Plan and Manage an Azure AI Solution | - Plan solution requirements and architecture - Select appropriate Azure AI services - Manage security, compliance, and responsible AI |
| Topic 3: Implement Natural Language Processing Solutions | - Translate and interpret language using Azure AI services - Implement question answering and conversational AI - Analyze text using Azure AI Language |
| Topic 4: Implement Generative AI Solutions | - Implement Azure OpenAI Service solutions - Integrate prompt engineering techniques - Build retrieval-augmented generation (RAG) solutions |
| Topic 5: Implement Computer Vision Solutions | - Implement custom vision models - Analyze images and videos using Azure AI Vision - Extract information using OCR and form recognition |
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