AI-102: Designing and Implementing an Azure AI Solution Course Outline
Overview
AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. The course will use C# or Python as the programming language.
Who Should Attend?
Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure.
Course Prerequisites
Before attending this course, students must have:
Knowledge of Microsoft Azure and ability to navigate the Azure portal
Knowledge of either C# or Python
Familiarity with JSON and REST programming semantics
Recommended course prerequisites
AI-900T00: Microsoft Azure AI Fundamentals course
Course Outline
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 OpenAI 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 and remove background
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 - Custom named entity recognition
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 Form Recognizer 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 - Implement Retrieval Augmented Generation (RAG) with Azure OpenAI Service
Understand Retrieval Augmented Generation (RAG) with Azure OpenAI Service
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
View outline in Word
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