Artificial Intelligence (AI) is increasingly at the core of modern apps and services. In this module, you ll learn about some common AI capabilities that you can leverage in your apps, and how those capabilities are implemented in Microsoft Azure. You ll also learn about some considerations for designing and implementing AI solutions responsibly.
Lessons
After completing this module, students will be able to:
Cognitive Services are the core building blocks for integrating AI capabilities into your apps. In this module, you ll learn how to provision, secure, monitor, and deploy cognitive services.
Lessons
After completing this module, students will be able to:
Natural Language processing (NLP) is a branch of artificial intelligence that deals with extracting insights from written or spoken language. In this module, you ll learn how to use cognitive services to analyze and translate text.
Lessons
Lab:
After completing this module, students will be able to:
Many modern apps and services accept spoken input and can respond by synthesizing text. In this module, you ll continue your exploration of natural language processing capabilities by learning how to build speech-enabled applications.
Lessons
Lab:
Lab : Recognize and Synthesize Speech
Lab : Translate Speech
After completing this module, students will be able to:
To build an application that can intelligently understand and respond to natural language input, you must define and train a model for language understanding. In this module, you ll learn how to use the Language Understanding service to create an app that can identify user intent from natural language input.
Lessons
Lab:
After completing this module, students will be able to:
One of the most common kinds of interaction between users and AI software agents is for users to submit questions in natural language, and for the AI agent to respond intelligently with an appropriate answer. In this module, you ll explore how the QnA Maker service enables the development of this kind of solution.
Lessons
Lab: Create a QnA Solution
After completing this module, students will be able to:
Bots are the basis for an increasingly common kind of AI application in which users engage in conversations with AI agents, often as they would with a human agent. In this module, you ll explore the Microsoft Bot Framework and the Azure Bot Service, which together provide a platform for creating and delivering conversational experiences.
Lessons
Lab:
After completing this module, students will be able to:
Computer vision is an area of artificial intelligence in which software applications interpret visual input from images or video. In this module, you ll start your exploration of computer vision by learning how to use cognitive services to analyze images and video.
Lessons
Lab:
After completing this module, students will be able to:
While there are many scenarios where pre-defined general computer vision capabilities can be useful, sometimes you need to train a custom model with your own visual data. In this module, you ll explore the Custom Vision service, and how to use it to create custom image classification and object detection models.
Lessons
Lab:
After completing this module, students will be able to:
Facial detection, analysis, and recognition are common computer vision scenarios. In this module, you ll explore the user of cognitive services to identify human faces.
Lessons
Lab : Detect, Analyze, and Recognize Faces
After completing this module, students will be able to:
Optical character recognition (OCR) is another common computer vision scenario, in which software extracts text from images or documents. In this module, you ll explore cognitive services that can be used to detect and read text in images, documents, and forms.
Lessons
Lab:
After completing this module, students will be able to:
Ultimately, many AI scenarios involve intelligently searching for information based on user queries. AI-powered knowledge mining is an increasingly important way to build intelligent search solutions that use AI to extract insights from large repositories of digital data and enable users to find and analyze those insights.
Lessons
Lab:
After completing this module, students will be able to: