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.
Learning Path 1: Prepare for AI engineering
AI Engineers design and develop intelligent solutions that encapsulate artificial intelligence (AI) capabilities. As an aspiring Azure AI Engineer, it's important to understand some of the key foundational concepts on which AI is based, and the various services in Microsoft Azure that you can use to build AI solutions.
- Prepare to develop AI solutions on Azur3
Learning Path 2: Provision and manage Azure Cognitive Services
Azure Cognitive Services are building blocks of AI functionality that you can integrate into your applications. In this learning path, you'll learn how to provision, secure. monitor, and deploy cognitive services resources and use them to build intelligent solutions.
- Create and consume Cognitive Services
- Secure Cognitive Services
- Monitor Cognitive Services
- Deploy cognitive services in containers
Learning Path 3: Process and translate text with Azure Cognitive Services
A large volume of the data that applications need to process is in text format. Using Azure Cognitive Services, you can create apps that extract semantic meaning from text and translate it between languages.
- Extract insights from text with the Language service
- Translate text with the Translator service
Learning Path 4: Process and Translate Speech with Azure Cognitive Speech Services
Learn how to develop speech-enabled applications by using the Speech service.
- Create speech-enabled apps with the Speech service
- Translate speech with the speech service
Learning Path 5: Create a Language Understanding solution with Azure Cognitive Services
Natural language processing (NLP) solutions use language models to interpret the semantic meaning of written or spoken language. You can use the Language Understanding service to build language models for your applications.
- Build a Language Understanding model
- Publish and use a Language Understanding app
Learning Path 6: Build a question answering solution
A common pattern for intelligent apps is to enable users to ask questions using natural language, and receive appropriate answers. This kind of solution brings conversational intelligence to a traditional frequently asked questions (FAQ) publication.
- Build a question answering solution
Learning Path 7: Create conversational AI solutions
Conversational AI solutions are based on interactions between human users and AI agents called bots. In this learning path, you'll learn how to build bots that can be delivered on Microsoft Azure.
- Create a bot with the Bot Framework SDK
- Create a Bot with the Bot Framework Composer
Learning Path 8: Create computer vision solutions with Azure Cognitive Services
Computer vision is an area of artificial intelligence that deals with visual perception. Azure Cognitive Services include multiple services that support common computer vision scenarios.
- Analyze images
- Analyze video
- Classify images
- Detect objects in images
- Detect, analyze, and recognize faces
Learning Path 9: Extract text from images and documents
Learn how to implement text extraction solutions with images and documents using form recognizer service's OCR Test Tool, pre-built models, and custom models.
- Read Text in Images and Documents with the Computer Vision Service
- Extract data from forms with Form Recognizer
Learning Path 10: Implement knowledge mining with Azure Cognitive Search
Do you have information locked up in structured and unstructured data sources? Using Azure Cognitive Search, you can extract key insights from this data, and enable applications to search and analyze them.
- Create an Azure Cognitive Search solution
- Create a custom skill for Azure Cognitive Search
- Create a knowledge store with Azure Cognitive Search
- Enrich a search index using Language Studio
- Implement advanced search features in Azure Cognitive Search
- Build an Azure Machine Learning custom skill for Azure Cognitive Search
- Search data outside the Azure platform in Azure Cognitive Search using Azure Data Factory
- Maintain an Azure Cognitive Search solution
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.
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
To gain C# or Python skills, complete the free Take your first steps with C# or Take your first steps with Python learning path before attending the course.
If you are new to artificial intelligence, and want an overview of AI capabilities on Azure, consider completing the Azure AI Fundamentals certification before taking this one.
- Describe considerations for AI-enabled application development
- Create, configure, deploy, and secure Azure Cognitive Services
- Develop applications that analyze text
- Develop speech-enabled applications
- Create applications with natural language understanding capabilities
- Create QnA applications
- Create conversational solutions with bots
- Use computer vision services to analyze images and videos
- Create custom computer vision models
- Develop applications that detect, analyze, and recognize faces
- Develop applications that read and process text in images and documents
- Create intelligent search solutions for knowledge mining