The AI-102T00: Designing and Implementing a Microsoft Azure AI Solution is a comprehensive 4-day course. It is tailored for software developers or individuals aspiring to roles such as AI Engineers, aiming to enhance their skills in building AI-infused intelligent applications. This intermediate-level program, offered by Azure-certified experts at Vinsys, focuses on leveraging Microsoft Bot Framework, Azure AI Services, Azure AI Search, and Azure OpenAI. It will further equip you to understand natural language processing, recognize images, and more. You must have a working knowledge of C# or Python programming language. With flexible delivery options, including virtual instructor-led training, private group training, and traditional instructor-led training, Vinsys ensures you can choose the best format.
Our hands-on exercises in the AI-102T00 course provide a rich learning experience. By the end of the program, you will have gained practical skills ready for immediate application in real-world projects like AI application development. Moreover, Vinsys AI-102T00 course prepares you for the AI-102 exam required for earning the Microsoft Certified: Azure AI Engineer Associate credential. Join Vinsys and take the next step in mastering Azure AI solutions.
Loading...
Enroll in AI 102T00: Designing and Implementing a Microsoft Azure AI Solution to learn in-depth about Azure AI services, secure deployments, and responsible AI practices. With Vinsys' flexible and advanced learning options, you can choose instructor-led, self-paced, or blended options. By the end of the course, you will be equipped to:
● Understand responsible AI concepts, terminology, and considerations for application development.
● Explore capabilities of Azure Machine Learning, AI Services, Cognitive Search, and the Azure Bot Service.
● Analyze images, create smart-cropped thumbnails, and classify images using Azure AI Vision and Custom Vision.
● Detect, analyze, and recognize faces, implementing facial recognition in applications with Azure AI Vision.
● Build language understanding models, analyze text, and perform sentiment analysis using Azure AI-Language.
● Develop question-answering solutions, create knowledge bases, and enhance question-answering performance.
● Build conversational language understanding models using prebuilt capabilities of the Azure AI-Language service.
● Extract custom entities and train models for named entity extraction solutions in text.
● Learn about using Azure OpenAI Service for generative AI, including code generation, image generation, and responsible AI practices.
● Develop an understanding of utilizing Azure AI services, Azure AI Search, and Azure OpenAI for AI-infused applications.
● Learn to provision, secure, and monitor Azure AI services, emphasizing authentication and network security.
● Software engineers specializing in building, managing, and deploying AI solutions using Azure AI Services, Azure AI Search, and Azure OpenAI.
● Data Scientists aiming to improve their skills in AI development.
● AI Engineers looking for extended knowledge in deploying AI solutions on the Azure platform.
● Aspiring Microsoft Azure AI Engineer Associate certification candidates.
It is advisable to have a prior understanding of the AI-900T00: Microsoft Azure AI Fundamentals. Moreover, these are other suggested prerequisites for the course:
● Familiarity with Microsoft Azure and understanding of Azure portal navigation.
● Experience in JSON and familiarity with REST programming semantics.
● Understanding of C# or Python and experience in utilizing REST-based APIs for language analysis, computer vision, and intelligent search on Azure
● Define artificial intelligence
● Understand AI-related terms
● Understand considerations for AI Engineers
● Understand considerations for responsible AI
● Understand the capabilities of Azure Machine Learning
● Understand the capabilities of Azure AI Services
● Understand the capabilities of the Azure Bot Service
● Understand the capabilities of Azure Cognitive Search
● Provision an Azure AI services resource
● Identify endpoints and keys
● Use a REST API
● Use an SDK
● Exercise - Use Azure AI services
● Consider authentication
● Implement network security
● Exercise - Manage Azure AI Services Security
● Monitor cost
● Create alerts
● View metrics
● Manage diagnostic logging
● Exercise - Monitor Azure AI services
● Understand containers
● Use Azure AI services containers
● Exercise - Use a container
● Provision an Azure AI Vision resource
● Analyze an image
● Generate a smart-cropped thumbnail
● Exercise - Analyze images with Azure AI Vision
● Provision Azure resources for Azure AI Custom Vision
● Understand image classification
● Train an image classifier
● Exercise - Classify images with Azure AI Custom Vision
● Identify options for face detection analysis and identification
● Understand considerations for face analysis
● Detect faces with the Azure AI Vision service
● Understand the capabilities of the face service
● Compare and match detected faces
● Implement facial recognition
● Exercise - Detect, analyze, and identify faces
● Explore Azure AI Vision options for reading text
● Use the Read API
● Exercise - Read the text in images
● Understand Azure Video Indexer capabilities
● Extract custom insights
● Use Video Analyzer widgets and APIs
● Exercise - Analyze video
● Provision an Azure AI-language resource
● Detect language
● Extract key phrases
● Analyze sentiment
● Extract entities
● Extract linked entities
● Exercise - Analyze text
● Understand question answering
● Compare question answering to Azure AI-language understanding
● Create a knowledge base
● Implement multi-turn conversation
● Test and publish a knowledge base
● Use a knowledge base
● Improve question-answering performance
● Exercise - Create a question-answering solution
● Understand the prebuilt capabilities of the Azure AI-language service
● Understand resources for building a conversational language understanding model
● Define intents, utterances, and entities
● Use patterns to differentiate similar utterances
● Use prebuilt entity components
● Train, test, publish, and review a conversational language understanding model
● Exercise - Build an Azure AI services conversational language understanding model
● Understand the types of classification projects
● Understand how to build text classification projects
● Exercise - Classify text
● Understand custom-named entity recognition
● Label your data
● Train and evaluate your model
● Exercise - Extract custom entities
● Provision an Azure AI Translator resource
● Understand language detection, translation, and transliteration
● Specify translation options
● Define custom translations
● Exercise - Translate text with the Azure AI Translator service
● Provision an Azure resource for speech
● Use the Azure AI Speech-to-Text API
● Use the text-to-speech API
● Configure audio format and voices
● Use Speech Synthesis Markup Language
● Exercise - Create a speech-enabled app
● Provision an Azure resource for speech translation
● Translate speech to text
● Synthesize translations
● Exercise - Translate speech
● Manage capacity
● Understand search components
● Understand the indexing process
● Search an index
● Apply filtering and sorting
● Enhance the index
● Exercise - Create a search solution
● Create a custom skill
● Add a custom skill to a skillset
● Exercise - Implement a custom skill
● Define projections
● Define a knowledge store
● Exercise - Create a knowledge store
● Understand AI Document Intelligence
● Plan Azure AI Document Intelligence resources
● Choose a model type
● Understand prebuilt models
● Use the General Document, Read, and Layout models
● Use financial, ID, and tax models
● Exercise - Analyze a document using Azure AI Document Intelligence
● What is Azure Document Intelligence?
● Get started with Azure Document Intelligence
● Train custom models
● Use Azure Document Intelligence models
● Use the Azure Document Intelligence Studio
● Exercise - Extract data from custom form
● Access Azure OpenAI Service
● Use Azure OpenAI Studio
● Explore types of generative AI models
● Deploy generative AI models
● Use prompts to get completions from models
● Test models in Azure OpenAI Studio's playgrounds
● Exercise - Get started with Azure OpenAI Service
● Integrate Azure OpenAI into your app
● Use Azure OpenAI REST API
● Use Azure OpenAI SDK
● Exercise - Integrate Azure OpenAI into your app
● Understand prompt engineering
● Write more effective prompts
● Provide context to improve accuracy
● Exercise - Utilize prompt engineering in your application
● Construct code from natural language
● Complete code and assist the development process
● Fix bugs and improve your code
● Exercise - Generate and improve code with Azure OpenAI Service
● What is DALL-E?
● Explore DALL-E in Azure OpenAI Studio
● Use the Azure OpenAI REST API to consume DALL-E models
● Exercise - Generate images with a DALL-E model
● Understand how to use your data
● Add your data source
● Chat with your model using your data
● Exercise - Use your data with Azure OpenAI Service
● Plan a responsible generative AI solution
● Identify potential harms
● Measure potential harms
● Mitigate potential harms
● Operate a responsible generative AI solution
● Exercise - Explore content filters in Azure OpenAI
The AI-102: Designing and Implementing an Azure AI Solution Certification
The AI-102T00 course is a rigorous preparation for the AI-102 exam. This assessment is required to obtain the prestigious Microsoft Certified: Azure AI Engineer Associate credential.
Upon successful exam completion, you will earn this industry-recognized validation of your subject matter expertise in designing, implementing, and operationalizing sophisticated AI solutions on the Microsoft Azure platform. This credential will underscore your ability to leverage Azure's intelligent services, intuitive search capabilities, and the Microsoft Bot Framework to build and deploy groundbreaking AI applications.
What's the difference between the AI-102T00 course and the AI-102 exam?
The AI-102T00 course equips you with the knowledge and skills needed to pass the exam. Microsoft administers the exam and validates your competency in building and deploying AI solutions on Azure.
Why should I choose Vinsys for the AI-102T00 course?
Our 25-year legacy of delivering successful tech training speaks for itself. We combine globally recognized Azure expertise with proven training methodologies and a focus on practical application.
How does Vinsys ensure my success on the exam?
We provide access to practice exams, study guides, and ongoing support from our expert instructors. Our comprehensive course thoroughly prepares you to showcase your mastery of Azure AI.
Does Vinsys offer any additional resources beyond the course?
Yes, we provide access to exclusive guides and recorded sessions for review. You will also have 24/7 access to our expert Vinsys team for Q&A sessions and individual support.
Will this AI-102T00 course help me build AI solutions?
Our curriculum focuses on practical application, aligning with current industry trends and challenges. You will graduate with the skills to design and deploy cutting-edge AI solutions.
What certification does the AI-102T00 course prepare for?
The AI-102 course prepares you for the Microsoft Certified: Azure AI Engineer Associate credential, a globally recognized certification.
Can I pursue the AI-102T00 course as an AI enthusiast?
Yes, the course is suitable for both software developers and AI enthusiasts seeking to deepen their knowledge. However, you must be aware of Azure portal navigation.
What is the Microsoft Azure certification exam AI-102 about?
The Microsoft Azure certification exam AI-102 assesses your proficiency in planning and managing Azure cognitive services, implementing computer vision, natural language processing, knowledge mining, and conversational AI solutions.
What learning formats does Vinsys offer for the course?
Vinsys provides a hybrid learning model, such as virtual instructor-led, private group, and instructor-led training options for flexible learning.