At course completion

After completing this course, students will be able to:

• Explain machine learning, and how algorithms and languages are used
• Describe the purpose of Azure Machine Learning, and list the main features of Azure Machine Learning Studio
• Upload and explore various types of data to Azure Machine Learning
• Explore and use techniques to prepare datasets ready for use with Azure Machine Learning
• Explore and use feature engineering and selection techniques on datasets that are to be used with Azure Machine Learning
• Explore and use regression algorithms and neural networks with Azure Machine Learning
• Explore and use classification and clustering algorithms with Azure Machine Learning
• Use R and Python with Azure Machine Learning, and choose when to use a particular language
• Explore and use hyperparameters and multiple algorithms and models, and be able to score and evaluate models
• Explore how to provide end-users with Azure Machine Learning services, and how to share data generated from Azure Machine Learning models
• Explore and use the Cognitive Services APIs for text and image processing, to create a recommendation application, and describe the use of neural networks with Azure Machine Learning
• Explore and use HDInsight with Azure Machine Learning
• Explore and use R and R Server with Azure Machine Learning, and explain how to deploy and configure SQL Server to support R services