This course runs for a duration of 4 days.
The class will run daily from 8 AM ET to 4 PM ET.
Class Location: Virtual LIVE Instructor Led - Virtual Live Classroom.
AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. The course will use C# or Python as the programming language.
Audience profile
Software engineers concerned with building, managing and deploying AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. 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 conversational AI solutions on Azure.
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 AI 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 - Use AI responsibly with Azure AI Content Safety
What is Content Safety
How does Azure AI Content Safety work?
When to use Azure AI Content Safety
7 - Analyze images
Provision an Azure AI Vision resource
Analyze an image
Generate a smart-cropped thumbnail and remove background
8 - Image classification with custom Azure AI Vision models
Understand custom model types
Create a custom project
Label and train a custom model
9 - Classify images
Provision Azure resources for Azure AI Custom Vision
Understand image classification
Train an image classifier
10 - Detect objects in images
Understand object detection
Train an object detector
Consider options for labeling images
11 - 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
12 - Read Text in images and documents with the Azure AI Vision Service
Explore Azure AI Vision options for reading text
Use the Read API
13 - Analyze video
Understand Azure Video Indexer capabilities
Extract custom insights
Use Video Analyzer widgets and APIs
14 - Analyze text with Azure AI Language
Provision an Azure AI Language resource
Detect language
Extract key phrases
Analyze sentiment
Extract entities
Extract linked entities
15 - Create question answering solutions with Azure AI Language
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
16 - 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
17 - Create a custom text classification solution
Understand types of classification projects
Understand how to build text classification projects
18 - Custom named entity recognition
Understand custom named entity recognition
Label your data
Train and evaluate your model
19 - Translate text with Azure AI Translator service
Provision an Azure AI Translator resource
Specify translation options
Define custom translations
20 - 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
21 - Translate speech with the Azure AI Speech service
Provision an Azure resource for speech translation
Translate speech to text
Synthesize translations
22 - 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
23 - Create a custom skill for Azure AI Search
Define the custom skill schema
Add a custom skill
Custom text classification skill
Machine learning custom skill
24 - Create a knowledge store with Azure AI Search
Define projections
Define a knowledge store
25 - 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
26 - Search data outside the Azure platform in Azure AI Search using Azure Data Factory
Index data from external data sources using Azure Data FactoryIndex any data using the Azure AI Search push API
27 - Maintain an Azure AI Search solution
Manage security of an Azure AI Search solution
Optimize performance of an Azure AI Search solution
Manage costs of an Azure AI Search solution
Improve reliability of an Azure AI Search solution
Monitor an Azure AI Search solution
Debug search issues using the Azure portal
28 - Perform search reranking with semantic ranking in Azure AI Search
What is semantic ranking?
Set up semantic ranking
29 - Perform vector search and retrieval in Azure AI Search
What is vector search?
Prepare your search
Understand embedding
30 - Plan an Azure AI Document Intelligence solution
Understand AI Document Intelligence
Plan Azure AI Document Intelligence resources
Choose a model type
31 - Use prebuilt Document intelligence models
Understand prebuilt models
Use the General Document, Read, and Layout models
Use financial, ID, and tax models
32 - 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
33 - Create a composed Document intelligence model
Understand composed models
Assemble composed models
34 - Get started with Azure OpenAI Service
Access Azure OpenAI Service
Use Azure AI Studio
Explore types of generative AI models
Deploy generative AI models
Use prompts to get completions from models
Test models in Azure AI Studio's playground
35 - Build natural language solutions with Azure OpenAI Service
Integrate Azure OpenAI into your app
Use Azure OpenAI REST API
Use Azure OpenAI SDK
36 - Apply prompt engineering with Azure OpenAI Service
Understand prompt engineering
Write more effective prompts
Provide context to improve accuracy
37 - Generate code with Azure OpenAI Service
Construct code from natural language
Complete code and assist the development process
Fix bugs and improve your code
38 - Generate images with Azure OpenAI Service
What is DALL-E?
Explore DALL-E in Azure AI Studio
Use the Azure OpenAI REST API to consume DALL-E models
39 - 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
Before attending this course, students must have:
