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
- United State - 120,000 USD
- Europe - 90,547 EURO
- India - 20,00,327 INR
- England - 90,532 POUND
AI-102: Designing and Implementing an Azure AI Solution Certification Path
The Microsoft Designing and Implementing an Azure AI Solution Certification includes only one AI-100 Exam.
Microsoft AI-102 Exam Syllabus Topics:
| Topic | Details |
|---|---|
Plan and Manage an Azure Cognitive Services Solution (15-20%) | |
| Select the appropriate Cognitive Services resource | - select the appropriate cognitive service for a vision solution - select the appropriate cognitive service for a language analysis solution - select the appropriate cognitive Service for a decision support solution - select the appropriate cognitive service for a speech solution |
| Plan and configure security for a Cognitive Services solution | - manage Cognitive Services account keys - manage authentication for a resource - secure Cognitive Services by using Azure Virtual Network - plan for a solution that meets responsible AI principles |
| Create a Cognitive Services resource | - create a Cognitive Services resource - configure diagnostic logging for a Cognitive Services resource - manage Cognitive Services costs - monitor a cognitive service - implement a privacy policy in Cognitive Services |
| Plan and implement Cognitive Services containers | - identify when to deploy to a container - containerize Cognitive Services (including Computer Vision API, Face API, Languages, Speech, Form Recognizer) - deploy Cognitive Services Containers in Microsoft Azure |
Implement Computer Vision Solutions (20-25%) | |
| Analyze images by using the Computer Vision API | - retrieve image descriptions and tags by using the Computer Vision API - identify landmarks and celebrities by using the Computer Vision API - detect brands in images by using the Computer Vision API - moderate content in images by using the Computer Vision API - generate thumbnails by using the Computer Vision API |
| Extract text from images | - extract text from images or PDFs by using the Computer Vision service - extract information using pre-built models in Form Recognizer - build and optimize a custom model for Form Recognizer |
| Extract facial information from images | - detect faces in an image by using the Face API - recognize faces in an image by using the Face API - analyze facial attributes by using the Face API - match similar faces by using the Face API |
| Implement image classification by using the Custom Vision service | - label images by using the Computer Vision Portal - train a custom image classification model in the Custom Vision Portal - train a custom image classification model by using the SDK - manage model iterations - evaluate classification model metrics - publish a trained iteration of a model - export a model in an appropriate format for a specific target - consume a classification model from a client application - deploy image classification custom models to containers |
| Implement an object detection solution by using the Custom Vision service | - label images with bounding boxes by using the Computer Vision Portal - train a custom object detection model by using the Custom Vision Portal - train a custom object detection model by using the SDK - manage model iterations - evaluate object detection model metrics - publish a trained iteration of a model - consume an object detection model from a client application - deploy custom object detection models to containers |
| Analyze video by using Azure Video Analyzer for Media (formerly Video Indexer) | - process a video - extract insights from a video - moderate content in a video - customize the Brands model used by Video Indexer - customize the Language model used by Video Indexer by using the Custom Speech service - customize the Person model used by Video Indexer - extract insights from a live stream of video data |
Implement Natural Language Processing Solutions (20-25%) | |
| Analyze text by using the Language service | - retrieve and process key phrases - retrieve and process entity information (people, places, urls, etc.) - retrieve and process sentiment - detect the language used in text |
| Manage speech by using the Speech service | - implement text-to-speech - customize text-to-speech - implement speech-to-text - improve speech-to-text accuracy - improve text-to-speech accuracy - implement intent recognition |
| Translate language | - translate text by using the Translator service - translate speech-to-speech by using the Speech service - translate speech-to-text by using the Speech service |
| Build a initial language model by using Language Understanding Service (LUIS) | - create intents and entities based on a schema, and add utterances - create complex hierarchical entities
- train and deploy a model |
| Iterate on and optimize a language model by using Language Understanding | - implement phrase lists - implement a model as a feature (i.e. prebuilt entities) - manage punctuation and diacritics - implement active learning - monitor and correct data imbalances - implement patterns |
| Manage a Language Understanding model | - manage collaborators - manage versioning - publish a model through the portal or in a container - export a LUIS package - deploy a LUIS package to a container - integrate Bot Framework (LUDown) to run outside of the LUIS portal |
| Create a Questions Answering solution using the Language service | - create a question answering project - import questions and answers - train and test a knowledge base - publish a knowledge base - create a multi-turn conversation - add alternate phrasing - add chit-chat to a knowledge base- export a knowledge base - add active learning to a knowledge base |
Implement Knowledge Mining Solutions (15-20%) | |
| Implement a Cognitive Search solution | - create data sources - define an index - create and run an indexer - query an index - configure an index to support autocomplete and autosuggest - boost results based on relevance - implement synonyms |
| Implement an enrichment pipeline | - attach a Cognitive Services account to a skillset - select and include built-in skills for documents - implement custom skills and include them in a skillset |
| Implement a knowledge store | - define file projections - define object projections - define table projections - query projections |
| Manage a Cognitive Search solution | - provision Cognitive Search - configure security for Cognitive Search - configure scalability for Cognitive Search |
| Manage indexing | - manage re-indexing - rebuild indexes - schedule indexing - monitor indexing - implement incremental indexing - manage concurrency - push data to an index - troubleshoot indexing for a pipeline |
Implement Conversational AI Solutions (15-20%) | |
| Design and implement conversation flow | - design conversation logic for a bot - create and evaluate *.chat file conversations by using the Bot Framework Emulator - choose an appropriate conversational model for a bot, including activity handlers and dialogs |
| Create a bot by using the Bot Framework SDK | - use the Bot Framework SDK to create a bot from a template - implement activity handlers and dialogs - use Turn Context - test a bot using the Bot Framework Emulator - deploy a bot to Azure |
| Create a bot by using the Bot Framework Composer | - implement dialogs - maintain state - implement logging for a bot conversation - implement prompts for user input - troubleshoot a conversational bot - test a bot - publish a bot - add language generation for a response - design and implement adaptive cards |
| Integrate Cognitive Services into a bot | - integrate a question answering model - integrate a LUIS service - integrate a Speech service resource |
Skills measured
- Implement Computer Vision solutions (20-25%)
- Implement knowledge mining solutions (15-20%)
- Plan and manage an Azure Cognitive Services solution (15-20%)
- Implement natural language processing solutions (20-25%)
- Implement conversational AI solutions (15-20%)
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
If you are still too lazy to be ambitious and have no clear career planning, when other people are busy at clearing Microsoft AI-102日本語 exam and hold a Azure AI Engineer Associate certification with AI-102日本語 exam dumps or exam prep, you will fall behind as the time passes. When an opportunity comes other people will have absolute advantages over you, you will miss this opportunity helplessly. Choosing our AI-102日本語 exam dumps & AI-102日本語 exam prep, be fighting like a hero! Don't be eased and lazy when you have to struggle with the most hard-working age. Get to the point, why is our AI-102日本語 (Designing and Implementing a Microsoft Azure AI Solution (AI-102日本語版)) exam dumps necessary for your real test?
◆ Based on AI-102日本語 Real Test
◆ Regularly Updated real test dumps
◆ Easy-to-read & Easy-to-handle Layout
◆ Well Prepared by Our Professional Experts
◆ Printable AI-102日本語 PDF for reading & writing
◆ Downloadable with no Limits
◆ 24 Hour On-line Support Available
◆ Free AI-102日本語 Download Demo PDF files
◆ One-year Service Warranty
◆ Money & Information guaranteed
Instant Download: Upon successful payment, Our systems will automatically send the product you have purchased to your mailbox by email. (If not received within 12 hours, please contact us. Note: don't forget to check your spam.)
Firstly, AI-102日本語 exam dumps can save a lot of money and time. As you know the official passing rate for AI-102日本語 is low, if you do not have valid exam preparation it will be difficult for you to pass. If you need two or more times to pass exam by yourselves, you can choose our AI-102日本語 exam dumps to pass exam at one attempt.
Secondly, if you choose our AI-102日本語 exam dumps, it is easy for you to make exam preparation for your exam that normally you just need to make sense of our real test dumps. It will only take you 1-2 days (15-30 hours) before real test. Comparing to paying a lot of attention on exams, AI-102日本語 exam dumps help you attend and pass exam easily.
Thirdly, we are actually sure that our AI-102日本語 exam dumps are valid and accurate; we are famous by our high-quality products, our passing rate of real test dumps is the leading position in this field. Our information resources about Microsoft AI-102日本語 are strong so that we always can get one-hand news. Our boss has considerable business acumen so that we always take a step ahead of others on releasing the latest AI-102日本語 exam dumps.
Fourthly, we have excellent staff with world-class service, if you purchase our AI-102日本語 exam dumps, you can enjoy our full-service. We are 7*24 on-line service support; whenever you have questions about our real test dumps we will reply you in two hours. If you have problem about payment or purchase wrong exam when you are purchasing our AI-102日本語 - Designing and Implementing a Microsoft Azure AI Solution (AI-102日本語版) exam dumps you can solve for you soon. After purchasing we will send you real test dumps in a minute by email. We provide one-year service warranty. We will send you the latest AI-102日本語 exam dumps always once it releases new version. It is same as that our exam prep is valid in one year. After one year if you want to extend the expired AI-102日本語 exam dumps we can give you 50% discount. Also if you want to purchase the other exam dumps, we will give you big discount as old customers.
If you have choice phobia disorder, do not hesitate now. Our AI-102日本語 exam dumps will be your best helper. We not only provide the best valid AI-102日本語 exam dumps & AI-102日本語 - Designing and Implementing a Microsoft Azure AI Solution (AI-102日本語版) exam prep but also try our best to serve for you.
