AI School

Bots allow customers to interact with applications in a conversational way using text, graphics, or speech. From a simple question and answer dialog, to sophisticated pattern matching and state tracking, learn how to build a chat bot with QnA Maker and LUIS.

Learn how to create bots for custom Microsoft Teams apps, allowing users to interact with your web service through text, interactive cards, and task modules. Bots can be a few simple commands, or complex virtual assistants powered by AI and natural language.

Most Bot Framework bots are built using the Bot Framework SDK, which organizes your bot and handles all conversations for you. An alternative to the SDK is to send messages directly to the bot using a REST API. You can send and receive messages with users on any channel.

Machine learning is the foundation for predictive modeling and artificial intelligence. Learn the principles of machine learning and how to use common tools to train, evaluate, and use machine learning models.

Learn how to implement computer vision by exploring how to process faces in images and video, detect objects, categorize images, extract insights with video indexer service, and implement custom vision solutions.

Learn how to implement Speech Services in Azure Cognitive Services, including speech-to-text transcription, synthesizing text input to speech, performing speech translation, and speaker recognition.

Learn how to extract and enhance indexable content from images, blobs, and other unstructured data by using pre-trained machine learning skillsets from the Cognitive Services Computer Vision and Text Analytics APIs.

Learn how to use Cognitive Language Services to analyze text, determine intent, detect adult themes, and process natural language with Azure Content Moderator and Language Understanding Intelligent Service (LUIS).

Learn how to use the Anomaly Detector API to monitor data over time and detect anomalies with machine learning. Get insight into your data, regardless of volume, industry, or scenario.

Machine teaching allows you to Infuse subject matter expertise into automated AI systems models. Use deep reinforcement learning to identify patterns and adapt behaviors. Leverage simulated environments for domain-specific use cases and scenarios.

Learn how autonomous systems combine human expertise with AI and ML through machine teaching. Learn how to automate management of DRL algorithms and models, and to integrate simulations for model optimization and scalability during training.

Project Bonsai is a low-code AI development platform. Learn how to improve production and reduce downtime with engineer-built AI that gives optimization guidance or makes independent decisions. Start using Inkling, the programming language for training AI.

Learn Microsoft guidelines for the development of responsible conversational AI, such as chat bots and voice-controlled systems. Learn the benefits of making bots transparent and trustworthy.

Learn how homomorphic encryption allows computation directly on encrypted data, making it easier to leverage the potential of the cloud for privacy-critical data.

Solutions to environmental challenges require substantial amounts of data, computing power, and expertise. The Microsoft AI for Earth initiative provides organizations with open data sets, cloud compute grants, open-source APIs, and education.

Explore the future from an alternative perspective with stories about how emerging technologies will impact our world.

Dive into interactive demos that showcase a selection of the capabilities of the Microsoft AI platform.

Get details, how-to, and code from our most popular projects and experiments, demonstrating the possibilities of AI.

Explore emerging cognitive capabilities with projects from Microsoft Research (MSR), including APIs and SDKs.