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Course 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 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 - Image classification with custom Azure AI Vision models
- Understand custom model types
- Create a custom project
- Label and train a custom model
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 - 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
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 - Enrich your data with Azure AI Language
- Explore the available features of Azure AI Language
- Enrich a search index in Azure AI Search with custom classes and Azure AI Language
23 - 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
24 - Build an Azure Machine Learning custom skill for Azure AI Search
- Understand how to use a custom Azure Machine Learning skillset
- Enrich a search index using an Azure Machine Learning model
25 - Search data outside the Azure platform in Azure AI Search using Azure Data Factory
- Index data from external data sources using Azure Data Factory
- Index any data using the Azure AI Search push API
26 - 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
27 - Perform search re-ranking with semantic ranking in Azure AI Search
- What is semantic ranking?
- Set up semantic ranking
28 - Perform vector search and retrieval in Azure AI Search
- What is vector search?
- Prepare your search
- Understand embedding
29 - Plan an Azure AI Document Intelligence solution
- Understand AI Document Intelligence
- Plan Azure AI Document Intelligence resources
- Choose a model type
30 - Use prebuilt Document intelligence models
- Understand prebuilt models
- Use the General Document, Read, and Layout models
- Use financial, ID, and tax models
31 - 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
32 - Create a composed Document intelligence model
- Understand composed models
- Assemble composed models
33 - Build a Document intelligence custom skill for Azure AI search
- Understand Azure AI Search enrichment pipelines
- Build an Azure AI Document Intelligence custom skill
34 - 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
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 OpenAI 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
40 - 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