AI-102T00: Develop AI solutions in Azure Training

Prepare to develop AI solutions on Azure

• Define artificial intelligence
• Understand AI-related terms
• Understand considerations for AI Engineers
• Understand considerations for responsible AI
• Understand capabilities of Azure Machine Learning
• Understand capabilities of Azure AI Services
• Understand capabilities of Azure OpenAI Service
• Understand capabilities of Azure AI Search

Create and consume Azure AI services

• Create Azure AI services resources in an Azure subscription.
• Identify endpoints, keys, and locations required to consume an Azure AI services resource.
• Use a REST API and an SDK to consume Azure AI services.

Secure Azure AI services

• Consider authentication for Azure AI services
• Manage network security for Azure AI services

Monitor Azure AI services

• Monitor Azure AI services costs.
• Create alerts and view metrics for Azure AI services.
• Manage Azure AI services diagnostic logging.

Deploy Azure AI services in containers

• Create containers for reuse
• Deploy to a container and secure a container
• Consume Azure AI services from a container

Analyze images

• Provision an Azure AI Vision resource
• Analyze an image
• Generate a smart-cropped thumbnail

Image classification with custom Azure AI Vision models

• Create a custom Azure AI Vision classification model
• Understand image classification
• Understand object detection
• Train an image classifier in Vision Studio

Detect, analyze, and recognize faces

• Identify options for face detection, analysis, and identification.
• Understand considerations for face analysis.
• Detect faces with the Computer Vision service.
• Understand capabilities of the Face service.
• Compare and match detected faces.
• Implement facial recognition.

Read Text in images and documents with the Azure AI Vision Service

• Read text from images using OCR
• Use the Azure AI Vision service Image Analysis with SDKs and the REST API
• Develop an application that can read printed and handwritten text

Analyze video

• Describe Azure Video Indexer capabilities
• Extract custom insights
• Use Azure Video Indexer widgets and APIs

Analyze text with Azure AI Language

• Detect language from text
• Analyze text sentiment
• Extract key phrases, entities, and linked entities

Create question answering solutions with Azure AI Language

• Understand question answering and how it compares to language understanding.
• Create, test, publish, and consume a knowledge base.
• Implement multi-turn conversation and active learning.
• Create a question answering bot to interact with using natural language.

Build a conversational language understanding model

• Provision Azure resources for Azure AI Language resource
• Define intents, utterances, and entities
• Use patterns to differentiate similar utterances
• Use pre-built entity components
• Train, test, publish, and review an Azure AI Language model

Create a custom text classification solution

• Understand types of classification projects
• Build a custom text classification project
• Tag data, train, and deploy a model
• Submit classification tasks from your own app

Custom named entity recognition

• Understand tagging entities in extraction projects
• Understand how to build entity recognition projects

Translate text with Azure AI Translator service

• Provision a Translator resource
• Understand language detection, translation, and transliteration
• Specify translation options
• Define custom translations

Create speech-enabled apps with Azure AI services

• Provision an Azure resource for the Azure AI Speech service
• Use the Azure AI Speech to text API to implement speech recognition
• Use the Text to speech API to implement speech synthesis
• Configure audio format and voices
• Use Speech Synthesis Markup Language (SSML)

Translate speech with the Azure AI Speech service

• Provision Azure resources for speech translation.
• Generate text translation from speech.
• Synthesize spoken translations.

Create an Azure AI Search solution

• Create an Azure AI Search solution
• Develop a search application

Create a custom skill for Azure AI Search

• Implement a custom skill for Azure AI Search
• Integrate a custom skill into an Azure AI Search skillset

Create a knowledge store with Azure AI Search

• Create a knowledge store from an Azure AI Search pipeline
• View data in projections in a knowledge store

Enrich your data with Azure AI Language

• Use Azure AI Language to enrich Azure AI Search indexes.
• Enrich an AI Search index with custom classes.

Implement advanced search features in Azure AI Search

• Improve the ranking of a document with term boosting
• Improve the relevance of results by adding scoring profiles
• Improve an index with analyzers and tokenized terms
• Enhance an index to include multiple languages
• Improve search experience by ordering results by distance from a given reference point

Build an Azure Machine Learning custom skill for Azure AI Search

• Understand how to use a custom Azure Machine Learning skillset.
• Use Azure Machine Learning to enrich Azure AI Search indexes.

Search data outside the Azure platform in Azure AI Search using Azure Data Factory

• Use Azure Data Factory to copy data into an Azure AI Search Index
• Use the Azure AI Search push API to add to an index from any external data source

Maintain an Azure AI Search solution

• Use Language Studio to enrich Azure AI Search indexes
• Enrich an AI Search index with custom classes

Perform search re-ranking with semantic ranking in Azure AI Search

• Describe semantic ranking
• Set up semantic ranking
• Perform semantic ranking on an index

Perform vector search and retrieval in Azure AI Search

• Describe vector search
• Describe embeddings
• Run vector search queries using the REST API

Plan an Azure AI Document Intelligence solution

• Describe the components of an Azure AI Document Intelligence solution.
• Create and connect to Azure AI Document Intelligence resources in Azure.
• Choose whether to use a prebuilt, custom, or composed model.

Plan an Azure AI Document Intelligence solution

• Describe the components of an Azure AI Document Intelligence solution.
• Create and connect to Azure AI Document Intelligence resources in Azure.
• Choose whether to use a prebuilt, custom, or composed model.

Use prebuilt Document intelligence models

• Identify business problems that you can solve by using prebuilt models in Forms Analyzer.
• Analyze forms by using the General Document, Read, and Layout models.
• Analyze forms by using financial, ID, and tax prebuilt models.

Extract data from forms with Azure Document intelligence

• Identify how Document intelligence's layout service, prebuilt models, and custom models can automate processes.
• Use Document intelligence's capabilities with SDKs, REST API, and Document Intelligence Studio.
• Develop and test custom models.

Create a composed Document intelligence model

• Describe business problems that you would use custom models and composed models to solve.
• Train a custom model to obtain data from forms with unusual structures.
• Create a composed model that can analyze forms in multiple formats.

Build a Document intelligence custom skill for Azure AI search

• Describe how a custom skill can enrich content passed through an Azure AI Search pipeline.
• Build a custom skill that calls an Azure Forms Analyzer solution to obtain data from forms.

Get started with Azure OpenAI Service

• Create an Azure OpenAI Service resource and understand types of Azure OpenAI base models.
• Use the Azure AI Studio, console, or REST API to deploy a base model and test it in the Studio's playgrounds.
• Generate completions to prompts and begin to manage model parameters.

Build natural language solutions with Azure OpenAI Service

• Integrate Azure OpenAI into your application
• Differentiate between different endpoints available to your application
• Generate completions to prompts using the REST API and language specific SDKse

Apply prompt engineering with Azure OpenAI Service

• Understand the concept of prompt engineering and its role in optimizing Azure OpenAI models' performance.
• Know how to design and optimize prompts to better utilize AI models.
• Include clear instructions, request output composition, and use contextual content to improve the quality of the model's responses.

Generate code with Azure OpenAI Service

• Use natural language prompts to write code
• Build unit tests and understand complex code with AI models
• Generate comments and documentation for existing code

Generate images with Azure OpenAI Service

• Describe the capabilities of DALL-E in the Azure OpenAI service
• Use the DALL-E playground in Azure AI Studio
• Use the Azure OpenAI REST interface to integrate DALL-E image generation into your apps

Implement Retrieval Augmented Generation (RAG) with Azure OpenAI Service

• Describe the capabilities of Azure OpenAI on your data
• Configure Azure OpenAI to use your own data
• Use Azure OpenAI API to generate responses based on your own data

Fundamentals of Responsible Generative AI

• Describe an overall process for responsible generative AI solution development
• Identify and prioritize potential harms relevant to a generative AI solution
• Measure the presence of harms in a generative AI solution
• Mitigate harms in a generative AI solution
• Prepare to deploy and operate a generative AI solution responsibly

• Lab Environment Setup
• Enable Resource Providers
• Get Started with Azure AI Services
• Manage Azure AI Services Security
• Monitor Azure AI Services
• Use an Azure AI Services Container
• Analyze Text
• Translate Text
• Recognize and Synthesize Speech
• Translate Speech
• Create a language understanding model with the Azure AI Language service
• Create a Conversational Language Understanding Client Application
• Create a Question Answering Solution
• Create a Bot with the Bot Framework SDK
• Create a Bot with Bot Framework Composer
• Analyze Images with Azure AI Vision
• Analyze Video with Video Analyzer
• Classify Images with Azure AI Custom Vision
• Detect Objects in Images with Custom Vision
• Detect and Analyze Faces
• Read Text in Images
• Extract Data from Forms
• Create an Azure AI Search solution
• Create a Custom Skill for Azure AI Search
• Create a Knowledge Store with Azure AI Search

AI-102T00: Develop AI solutions in Azure Training focused towards software developers who are willing to work on building AI-infused applications that will be further leveraging Azure AI Services in the process.

?The AI 102 exam consists of 40-60 questions. These questions appear in different types such as MCQ, scenario-based, arranged in the sequence, drag and drop, mark review, and so on.

Professionals with AI-900 certification can land job roles like data scientist, AI engineer, Machine learning engineer, and more.

One should least score 700 or greater in order to pass the AI-102 examination.

Completing this certification with the required marks will help you to land job roles like Azure engineer, AI solution architect, and Machine learning engineer.