Learn how to turn unstructured text into useful insights with natural language processing and Azure AI. This course is Part 3 of the eight-part Microsoft AI Fundamentals AI-901 series. It introduces text analysis concepts, connects them to language models, and shows how Azure language capabilities support practical business applications. Start with the foundations of NLP, including tokenization, text preparation, statistical text analysis, and semantic language models. Explore how text analysis helps organizations work with customer reviews, support tickets, emails, and documents. You will examine core capabilities such as language detection, sentiment analysis, key phrase extraction, named entity recognition, summarization, and personally identifiable information (PII) redaction.
Then move from concepts to implementation. Learn about Azure AI NLP services and text analysis in Microsoft Foundry, review how client applications connect to language services, and explore the role of authentication, endpoints, SDKs, and structured results. The course also introduces NLP solution architecture and the considerations that shape useful language applications. Responsible AI is part of the learning journey. Consider bias and fairness in language models, differences in performance across user populations, and the importance of privacy and responsible handling of language data.
Reinforce your understanding with quizzes, Microsoft Learn exercise guidance, a simulation exercise, and a guided lab demonstration. The simulation lets you explore the workflow without an Azure subscription. To complete the live Azure lab yourself, you need an Azure subscription and access to the relevant services.
