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Build models and learn the various parameters involved in designing models. Learn about the real-world applications of ML models and also how to train, manage, scale, and track them on Azure. This course will give an introduction to Machine Learning and how to build and deploy models faster. Learn to develop end-to-end workflow pipelines to build and track your assets. This course presents you with the concept and framework of cloud computing and the various machine learning services in Azure. You will learn about the benefits of cloud computing and also explore the Data Visualization capabilities of Azure. By the end of the course, you will be able to build predictive models using Machine learning services on Azure.
With machine learning, a huge amount of information can be processed to make decisions based on logic and data collected. Azure is a cloud-based platform that allows training, deploying, and managing Machine Learning models and in this course, you will be exposed to various tools and interfaces that are used to work on Azure Machine Learning. Students will learn to work with data pipelines to build ML solutions and use the collected data for experimentation and model training while learning to create a workspace in Azure. Students will gain hands-on experience in training a model and also prepare data for analyzing and making predictions using Azure. Students will be also able to demonstrate their skills in using the various tools and interfaces that help to solve large data processing projects. Join the course in Machine learning on Azure and explore the Extracting, Transforming, Loading Capabilities of Azure and also learn to