The benefit of obtaining the AI-102: Designing and Implementing an Azure AI Solution Exam Certification
- 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 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 certified candidates will be confident and stand different from others as their skills are more trained than non-certified professionals.
- 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 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.
- 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
- 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 Certification provides practical experience to candidates from all the aspects to be a proficient worker in the organization.
- This certification credential will give you edge over other counterparts. Apart from knowledge from AI-102: Designing and Implementing an Azure AI Solution Exam.
Who should take the AI-102: Designing and Implementing an Azure AI Solution Exam
The AI-102 Exam certification is an internationally-recognized certification which help to have validation for Azure AI Solution Architects who have ability to accomplish the following technical tasks: analyze solution requirements; design solutions; integrate AI models into solutions; and deploy and manage solutions.
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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 AI models and services
- Select the appropriate data processing technologies
- Select the processing architecture for a solution
- Identify components and technologies required to connect service endpoints
- Identify automation requirements
Map security requirements to tools, technologies, and processes
- Identify processes and regulations needed to conform with data privacy, protection, and regulatory requirements
- Identify auditing 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 storage required to store logging, bot state data, and Cognitive Services output
- Identify appropriate services and tools for a solution
- Identify integration points with other Microsoft services
2. Design AI solutions (40-45%)
Design solutions that include one or more pipelines
- Design a strategy for ingest and egress data
- Design the integration point between multiple workflows and pipelines
- Define an AI application workflow process
- Design pipelines that use AI apps
- Select an AI solution that meet cost constraints
- Design pipelines that call Azure Machine Learning models
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
- Identify whether to use a cloud-based, on-premises, or hybrid compute infrastructure
- Select a compute solution that meets cost constraints
- Identify whether to create a GPU, FPGA, or CPU-based solution
Design for data governance, compliance, integrity, and security
- Ensure appropriate governance of data
- Ensure that data adheres to compliance requirements defined by your organization
- Design strategies to ensure that the solution meets data privacy regulations and industry standards
- 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
- Create solution endpoints
- Manage the flow of data through the solution components
- Implement data logging processes
- Develop AI pipelines
- Define and construct interfaces for custom AI services
- Develop streaming solutions
Integrate AI services with solution components
- Configure integration with Cognitive Services
- 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
Monitor and evaluate the AI environment
- Identify the differences between KPIs, reported metrics, and root causes of the differences
- Identify the differences between expected and actual workflow throughput
- Monitor AI components for availability
- Recommend changes to an AI solution based on performance data
- Maintain an AI solution for continuous improvement
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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