AI engineers and developers, especially at the intermediate level, are well aware of how important natural language processing (NLP) is for interpreting the meaning of written or spoken language. They also know that the Azure Cognitive ServicesLanguage Understanding serviceenables you to train a language model—with a relatively small number of samples—that apps can use to extract meaning from natural language. If you’re interested in exploring this AI tech further, I encourage you to take the Create a Language Understanding solution with Azure Cognitive Services learning path on Microsoft Learn. Find out how to use the Language Understanding service to create a language understanding app. Start with a model, and then define intents, utterances, and entities. Train, test, and publish the model, and consume your app from client applications. This learning path can also help you prepare for ExamAI-102: Designing and Implementing a Microsoft Azure AI Solution to earn the Microsoft Certified: Azure AI Engineer Associate certification. Say what you mean, with a Language Understanding solution, and continue to #LearnMicrosoftAI.