Read at any time
Many of our users have told us that they are really busy. Students have to take a lot of professional classes and office workers have their own jobs. They can only learn in some fragmented time. AI-102 training guide can meet your requirements. First, there are three versions of AI-102 learning materials and are not limited by the device. You don't need to worry about network problems either. You only need to use AI-102 exam questions for the first time in a network environment, after which you can be free from network restrictions. I know that many people like to write their own notes. The PDF version of AI-102 training guide is for you. The PDF version can be printed and you can carry it with you. If you have any of your own ideas, you can write it above. This can help you learn better.
Download immediately
If you decide to buy a product, you definitely want to use it right away! AI-102 training guide's powerful network and 24-hour online staff can meet your needs. First of all, we can guarantee that you will not encounter any obstacles in the payment process. After your payment is successful, we will send you an email within 5 to 10 minutes. As long as you click on the link, you can use AI-102 learning materials to learn. We know that time is really important to you. If you do not receive our email, you can contact our online customer service. We will solve your problem immediately and let you have AI-102 exam questions as soon as possible.
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 processing architecture for a solution
- Identify components and technologies required to connect service endpoints
- Select the appropriate data processing technologies
- Identify automation requirements
- Select the appropriate AI models and services
Map security requirements to tools, technologies, and processes
- 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
- Identify appropriate tools for a solution
- Identify auditing requirements
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
- Select an AI solution that meet cost constraints
- Define an AI application workflow process
- Design a strategy for ingest and egress data
- Design pipelines that call Azure Machine Learning models
- Design pipelines that use AI apps
- 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 bot services that use Language Understanding (LUIS)
- Integrate bots and AI solutions
- Integrate bots with Azure app services and Azure Application Insights
- 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 that data adheres to compliance requirements defined by your organization
- Define how users and applications will authenticate to AI services
- Ensure appropriate governance of data
- Design a content moderation strategy for data usage within an AI solution
- Design strategies to ensure that the solution meets data privacy regulations and industry standards
3. Implement and monitor AI solutions (25-30%)
Implement an AI workflow
- Develop AI pipelines
- Implement data logging processes
- Create solution endpoints
- Define and construct interfaces for custom AI services
- Manage the flow of data through the solution components
- Develop streaming solutions
Integrate AI services with solution components
- Configure prerequisite components and input datasets to allow the consumption of Cognitive Services APIs
- Implement Azure Search in a solution
- 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
- Identify the differences between expected and actual workflow throughput
- Recommend changes to an AI solution based on performance data
- Identify the differences between KPIs, reported metrics, and root causes of the differences
- Monitor AI components for availability
Exam Details
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.
I know you must want to get a higher salary, but your strength must match your ambition! The opportunity is for those who are prepared! AI-102 exam questions can help you improve your strength! You will master the most practical knowledge in the shortest possible time. It is also very easy if you want to get the Microsoft certificate. In the face of fierce competition, you should understand the importance of time. You must walk in front of the competitors. If you have more strength, you will get more opportunities. Your dream life can really become a reality! AI-102 learning materials are here, right to choose!
How much AI-102: Designing and Implementing an Azure AI Solution Exam Cost
The price of the Microsoft Mobility and Devices Fundamentals exam is $165 USD, for more information related to exam price please visit to Microsoft Training website as prices of Microsoft exams fees get varied country wise.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
Spend the least time
How much time do you think it takes to pass an exam? AI-102 learning materials can assure you that you only need to spend twenty to thirty hours to pass the exam. Many people think this is incredible. But AI-102 exam questions really did. We chose the most professional team, so our products have a comprehensive content and scientific design. Under the leadership of a professional team, we have created the most efficient learning AI-102 training guide for our users. Our users use their achievements to prove that we can get the most practical knowledge in the shortest time. AI-102 exam questions are tested by many users and you can rest assured. If you want to spend the least time to achieve your goals, AI-102 learning materials are definitely your best choice. You can really try it we will never let you down!
Microsoft AI-102 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Implement natural language processing solutions | 15-20% | - Perform text analysis, sentiment detection, and language detection - Build conversational AI and chatbots - Customize and deploy NLP models - Implement translation and summarization |
| Implement computer vision solutions | 10-15% | - Process and index video content - Integrate vision capabilities into applications - Extract text and handwriting from images - Build and deploy custom vision models - Analyze images and detect objects/features |
| Plan and manage an Azure AI solution | 20-25% | - Select suitable AI models - Plan solutions aligned with responsible AI principles - Monitor, optimize, and secure AI solutions - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Select appropriate Microsoft Foundry Services - Create and configure Azure AI resources |
| Implement generative AI solutions | 15-20% | - Implement model monitoring and feedback - Apply prompt engineering and fine-tuning - Integrate Azure OpenAI and other generative models - Orchestrate multiple models and containers - Deploy and manage generative models |
| Implement knowledge mining and information extraction solutions | 15-20% | - Build knowledge bases and search indexes - Ingest and process structured/unstructured data - Implement intelligent search and retrieval - Extract entities, relationships, and key phrases |
| Implement an agentic solution | 5-10% | - Develop multi-agent workflows and orchestration - Test, deploy, and optimize agents - Understand agent use cases and types - Build agents with Microsoft Foundry Agent Service |
