Module 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 Azure OpenAI Service
- Understand capabilities of Azure AI Search
Module 2 : Create and consume Azure AI services
- Create Azure AI services resources in an Azure subscription.
- Identify endpoints, keys, and locations required to consume an Azure AI services resource.
- Use a REST API and an SDK to consume Azure AI services.
Module 3 : Secure Azure AI services
- Consider authentication for Azure AI services
- Manage network security for Azure AI services
Module 4 : Monitor Azure AI services
- Monitor Azure AI services costs.
- Create alerts and view metrics for Azure AI services.
- Manage Azure AI services diagnostic logging.
Module 5 : Deploy Azure AI services in containers
- Create containers for reuse
- Deploy to a container and secure a container
- Consume Azure AI services from a container
Module 6 : Analyze images
- Provision an Azure AI Vision resource
- Analyze an image
- Generate a smart-cropped thumbnail
Module 7 : Classify images
- Provision Azure resources for Azure AI Custom Vision
- Understand image classification
- Train an image classifier
Module 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
Module 9 : Read Text in images and documents with the Azure AI Vision Service
- Read text from images using OCR
- Use the Azure AI Vision service Image Analysis with SDKs and the REST API
- Develop an application that can read printed and handwritten text
Module 10 : Analyze video
- Describe Azure Video Indexer capabilities
- Extract custom insights
- Use Azure Video Indexer widgets and APIs
Module 11 : Analyze text with Azure AI Language
- Detect language from text
- Analyze text sentiment
- Extract key phrases, entities, and linked entities
Module 12 : Create question answering solutions with Azure AI Language
- Understand question answering and how it compares to language understanding.
- Create, test, publish and consume a knowledge base
- Implement multi-turn conversation and active learning
- Create a question answering bot to interact with using natural language
Module 13 : Build a conversational language understanding model
- Provision Azure resources for Azure AI Language resource
- Define intents, utterances, and entities
- Use patterns to differentiate similar utterances
- Use pre-built entity components
- Train, test, publish, and review an Azure AI Language model
Module 14 : Create a custom text classification solution
- Understand types of classification projects
- Build a custom text classification project
- Tag data, train, and deploy a model
- Submit classification tasks from your own app
Module 15 : Custom named entity recognition
- Understand tagging entities in extraction projects
- Understand how to build entity recognition projects
Module 16 : Translate text with Azure AI Translator service
- Provision a Translator resource
- Understand language detection, translation, and transliteration
- Specify translation options
- Define custom translations
Module 17 : Create speech-enabled apps with Azure AI services
- Provision an Azure resource for the Azure AI Speech service
- Use the Azure AI Speech to text API to implement speech recognition
- Use the Text to speech API to implement speech synthesis
- Configure audio format and voices
- Use Speech Synthesis Markup Language (SSML)
Module 18 : Translate speech with the Azure AI Speech service
- Provision Azure resources for speech translation.
- Generate text translation from speech.
- Synthesize spoken translations.
Module 19 : Create an Azure AI Search solution
- Create an Azure AI Search solution
- Develop a search application
Module 20 : Create a custom skill for Azure AI Search
- Implement a custom skill for Azure AI Search
- Integrate a custom skill into an Azure AI Search skillset
Module 21 : Create a knowledge store with Azure AI Search
- Create a knowledge store from an Azure AI Search pipeline
- View data in projections in a knowledge store
Module 22 : Plan an Azure AI Document Intelligence solution
- Describe the components of an Azure AI Document Intelligence solution.
- Create and connect to Azure AI Document Intelligence resources in Azure.
- Choose whether to use a prebuilt, custom, or composed model.
Module 23 : Use prebuilt Form Recognizer models
- Identify business problems that you can solve by using prebuilt models in Forms Analyzer.
- Analyze forms by using the General Document, Read, and Layout models.
- Analyze forms by using financial, ID, and tax prebuilt models
Module 24 : Extract data from forms with Azure Document Intelligence
- Identify how Azure Document Intelligence's layout service, prebuilt models, and custom service can automate processes
- Use Azure Document Intelligence's Optical Character Recognition (OCR) capabilities with SDKs, REST API, and Azure Document Intelligence Studio
- Develop and test custom models
Module 25 : Get started with Azure OpenAI Service
- Create an Azure OpenAI Service resource and understand types of Azure OpenAI base models.
- Use the Azure OpenAI Studio, console, or REST API to deploy a base model and test it in the Studio's playgrounds.
- Generate completions to prompts and begin to manage model parameters.
Module 26 : Build natural language solutions with Azure OpenAI Service
- Integrate Azure OpenAI into your application
- Differentiate between different endpoints available to your application
- Generate completions to prompts using the REST API and language specific SDKs
Module 27 : Apply prompt engineering with Azure OpenAI Service
- Understand the concept of prompt engineering and its role in optimizing Azure OpenAI models' performance.
- Know how to design and optimize prompts to better utilize AI models.
- Include clear instructions, request output composition, and use contextual content to improve the quality of the model's responses.
Module 28 : Generate code with Azure OpenAI Service
- Use natural language prompts to write code
- Build unit tests and understand complex code with AI models
- Generate comments and documentation for existing code
Module 29 : Generate images with Azure OpenAI Service
- Describe the capabilities of DALL-E in the Azure openAI service
- Use the DALL-E playground in Azure OpenAI Studio
- Use the Azure OpenAI REST interface to integrate DALL-E image generation into your apps
Module 30 : Implement Retrieval Augmented Generation (RAG) with Azure OpenAI Service
- Describe the capabilities of Azure OpenAI on your data
- Configure Azure OpenAI to use your own data
- Use Azure OpenAI API to generate responses based on your own data
Module 31 : Fundamentals of Responsible Generative AI
- Describe an overall process for responsible generative AI solution development
- Identify and prioritize potential harms relevant to a generative AI solution
- Measure the presence of harms in a generative AI solution
- Mitigate harms in a generative AI solution
- Prepare to deploy and operate a generative AI solution responsibly