Microsoft R Server with Spark and HDI Insight

#About the Course The Microsoft Data Science Team invites you to an in-depth 2-day workshop on using Microsoft R for Data Science. In these sessions, you’ll gain hands-on experience with conducting scalable data analysis with Microsoft R Server. You will learn the fundamentals of R, and understand how Microsoft R Server addresses the major scalability and operationalization challenges associated with open source R. The final day will focus on Spark and HD Insight. The course is designed to help analysts integrate Microsoft R Server (MRS) into their data science toolbox, and integrate it with other tools in Azure and the Cortana Intelligence Suite. After completion, participants will be able to: * Explore and visualize data with R * Manipulate data that is too large to fit into memory with MRS * Train and test statistical models with high performance parallel external memory algorithms * Access data stored in Azure Blob Storage using Microsoft R Server (MRS) * Deploy Models as AzureML webservices # Prerequisites There are a few things you will need in order to properly follow the course materials: * We will assume you have already taken the following courses or have the background provided by these courses: * Implementing Real-Time Analytics with Hadoop in Azure HDInsight (or general knowledge of the Apache Hadoop ecosystem and HDInsight) * Data Science and Machine Learning Essentials (or general understanding of machine learning and predictive modeling) * Introduction to R for Data Science * Intermediate knowledge of R would be ideal, at the level of either of the following two courses: * Programming with R for Data Science * R for SAS Users Course #Modules The course is divided into the following modules: 1. The course is designed to help analysts integrate Microsoft R Server (MRS) into their data science toolbox, and integrate it with other tools in Azure and the Cortana Intelligence Suite. After completion, participants will be able to 2. Explore and visualize data with R 3. Manipulate data that is too large to fit into memory with MRS 4. Train and test statistical models with high performance parallel external memory algorithms 5. Access data stored in Azure Blob Storage using Microsoft R Server (MRS) 6. Deploy Models as AzureML webservices #Concepts Covered * Explore and visualize data with R * Manipulate data that is too large to fit into memory with MRS * Train and test statistical models with high performance parallel external memory algorithms * Access data stored in Azure Blob Storage using Microsoft R Server (MRS) * Deploy Models as AzureML webservices #Technologies Covered * Microsoft R Server and Spark