Booking options
£1,785
+ VAT£1,785
+ VATDelivered Online
All levels
Duration
4 Days
24 CPD hours
This course is intended for
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.
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.
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
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
Provision an Azure AI services resource
Identify endpoints and keys
Use a REST API
Use an SDK
Consider authentication
Implement network security
Monitor cost
Create alerts
View metrics
Manage diagnostic logging
Understand containers
Use Azure AI services containers
Provision an Azure AI Vision resource
Analyze an image
Generate a smart-cropped thumbnail
Provision Azure resources for Azure AI Custom Vision
Understand image classification
Train an image classifier
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
Explore Azure AI Vision options for reading text
Use the Read API
Understand Azure Video Indexer capabilities
Extract custom insights
Use Video Analyzer widgets and APIs
Provision an Azure AI Language resource
Detect language
Extract key phrases
Analyze sentiment
Extract entities
Extract linked entities
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
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
Understand types of classification projects
Understand how to build text classification projects
Understand custom named entity recognition
Label your data
Train and evaluate your model
Provision an Azure AI Translator resource
Specify translation options
Define custom translations
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
Provision an Azure resource for speech translation
Translate speech to text
Synthesize translations
Manage capacity
Understand search components
Understand the indexing process
Search an index
Apply filtering and sorting
Enhance the index
Create a custom skill
Add a custom skill to a skillset
Define projections
Define 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
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
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
Integrate Azure OpenAI into your app
Use Azure OpenAI REST API
Use Azure OpenAI SDK
Understand prompt engineering
Write more effective prompts
Provide context to improve accuracy
Construct code from natural language
Complete code and assist the development process
Fix bugs and improve your code
What is DALL-E?
Explore DALL-E in Azure OpenAI Studio
Use the Azure OpenAI REST API to consume DALL-E models
Understand how to use your own data
Add your own data source
Chat with your model using your own data
Plan a responsible generative AI solution
Identify potential harms
Measure potential harms
Mitigate potential harms
Operate a responsible generative AI solution
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