Catalog

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.

This 1-day course focuses on building intelligent applications that can see, interpret, and reason over images and documents using different multimodal models and agent-based tools. Learners explore how visual and document inputs can be combined with language models to enable structured extraction, analysis, and decision-making workflows. The course emphasizes practical patterns for extracting information, orchestrating tools, and grounding model responses in visual data.

This course prepares learners to design, implement, and operate Machine Learning Operations (MLOps) and Generative AI Operations (GenAIOps) solutions on Azure. It covers building secure and scalable AI infrastructure, managing the full lifecycle of traditional machine learning models with Azure Machine Learning, and deploying, evaluating, monitoring, and optimizing generative AI applications and agents using Microsoft Foundry. Learners will gain hands-on knowledge of automation, continuous integration and delivery, infrastructure as code, and observability by using tools such as GitHub Actions, Azure CLI, and Bicep. The course emphasizes collaboration with data science and DevOps teams to deliver reliable, production-ready AI systems aligned with modern MLOps and GenAIOps best practices.

Generative Artificial Intelligence (AI) is becoming more accessible through easy-to-use platforms like Azure AI Studio. Learn how to build generative AI applications like custom copilots that use language models and prompt flow to provide value to your users.

This learning path explores how the Azure AI and Azure Machine Learning Services integrations provided by the Azure AI extension for Azure Database for PostgreSQL – Flexible Server can enable you to build AI-powered apps.

Do you have information locked up in structured and unstructured data sources? Using Azure AI Search, you can extract key insights from this data, and enable applications to search and analyze them.

Get more done and unleash your creativity with Microsoft Copilot. In this learning path, you'll explore how to use Microsoft Copilot to help you research, find information, and generate effective content.

Generative Artificial Intelligence (AI) is becoming more functional and accessible, and AI agents are a key component of this evolution. This learning path will help you understand the AI agents, including when to use them and how to build them, using Azure AI Agent Service and Semantic Kernel Agent Framework. By the end of this learning path, you will have the skills needed to develop AI agents on Azure.

This course introduces fundamental concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. It teaches a mix of AI concepts and technology skills that are considered foundational to a successful career implementing AI solutions on Microsoft Azure.

Learn how to use the Semantic Kernel SDK to build intelligent applications that automate tasks and perform natural language processing.