Microsoft Artificial Intelligence Training (Training Course for AI 900 Exam)

This course aims to provide a comprehensive understanding of the common NLP workload scenarios. It covers a wide range of topics, including Key Phrase Extraction, Entity Recognition, Sentiment Analysis, Language Modeling, Speech Recognition and Synthesis, and Translation. The unit also introduces the capabilities of Azure AI Language Service and Azure AI Speech Service.

This course will equip the learners with knowledge about the unique aspects of AI workloads and the ethical considerations that are crucial in the development and use of AI systems. It’s a comprehensive guide that will help them navigate the complex landscape of AI. 

This course aims to provide a comprehensive understanding of the fundamental principles of machine learning techniques. It covers a wide range of topics, including common machine learning techniques such as supervised, unsupervised, reinforcement, and deep learning, as well as core concepts like data preprocessing, feature extraction, model training, validation, testing, and performance metrics. The unit also introduces the capabilities of Azure Machine Learning, a powerful tool for data wrangling, model development, and deployment. 

This course focuses on the features of computer vision workloads on Azure. It covers topics such as Image Classification Solutions, Object Detection Solutions, Optical Character Recognition Solutions, and Knowledge Mining Facial Detection and Facial Analysis Solutions. The unit also introduces the capabilities of Azure AI Vision Service and Azure AI Face Detection Service.

This course focuses on the features of generative AI workloads on Azure. It covers topics such as Features of Generative AI Models, Common Scenarios for Generative AI, and Responsible AI Considerations for Generative AI. The unit also introduces the capabilities of Azure OpenAI Service, including Natural Language Generation, Code Generation, and Image Generation.