AI-102T00 Designing and Implementing an Azure AI Solution

1 – 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 the Azure Bot Service
• Understand capabilities of Azure Cognitive Search

2 – Create and consume Azure AI services

• Provision an Azure AI services resource
• Identify endpoints and keys
• Use a REST API
• Use an SDK

3 – Secure Azure AI services

• Consider authentication
• Implement network security

4 – Monitor Azure AI services

• Monitor cost
• Create alerts
• View metrics
• Manage diagnostic logging

5 – Deploy Azure AI services in containers

• Understand containers
• Use Azure AI services containers

6 – Analyze images

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

7 – Classify images

• Provision Azure resources for Azure AI Custom Vision
• Understand image classification
• Train an image classifier

8 – Detect, analyze, and recognize faces

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

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

• Explore Azure AI Vision options for reading text
• Use the Read API

10 – Analyze video

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

11 – Analyze text with Azure AI Language

• Provision an Azure AI Language resource
• Detect language
• Extract key phrases
• Analyze sentiment
• Extract entities
• Extract linked entities

12 – Build a question answering solution

• 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

13 – Build a conversational language understanding model

• Understand 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 pre-built entity components
• Train, test, publish, and review a conversational language understanding model

14 – Create a custom text classification solution

• Understand types of classification projects
• Understand how to build text classification projects

15 – Create a custom named entity extraction solution

• Understand custom named entity recognition
• Label your data
• Train and evaluate your model

16 – Translate text with Azure AI Translator service

• Provision an Azure AI Translator resource
• Specify translation options
• Define custom translations

17 – Create speech-enabled apps with Azure AI services

• 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

18 – Translate speech with the Azure AI Speech service

• Provision an Azure resource for speech translation
• Translate speech to text
• Synthesize translations

19 – Create an Azure AI Search solution

• Manage capacity
• Understand search components
• Understand the indexing process
• Search an index
• Apply filtering and sorting
• Enhance the index

20 – Create a custom skill for Azure AI Search

• Create a custom skill
• Add a custom skill to a skillset

21 – Create a knowledge store with Azure AI Search

• Define projections
• Define a knowledge store

22 – Plan an Azure AI Document Intelligence solution

• Understand AI Document Intelligence
• Plan Azure AI Document Intelligence resources
• Choose a model type

23 – Use prebuilt Azure AI Document Intelligence models

• Understand prebuilt models
• Use the General Document, Read, and Layout models
• Use financial, ID, and tax models

24 – Extract data from forms with Azure 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

25 – Get started with Azure OpenAI Service

• 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

26 – Build natural language solutions with Azure OpenAI Service

• Integrate Azure OpenAI into your app
• Use Azure OpenAI REST API
• Use Azure OpenAI SDK

27 – Apply prompt engineering with Azure OpenAI Service

• Understand prompt engineering
• Write more effective prompts
• Provide context to improve accuracy

28 – Generate code with Azure OpenAI Service

• Construct code from natural language
• Complete code and assist the development process
• Fix bugs and improve your code

29 – Generate images 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

30 – Use your own data with Azure OpenAI Service

• Understand how to use your own data
• Add your own data source
• Chat with your model using your own data

31 – Fundamentals of Responsible Generative AI

• Plan a responsible generative AI solution
• Identify potential harms
• Measure potential harms
• Mitigate potential harms
• Operate a responsible generative AI solution