In this workshop you’ll cover a series of modules that guide you from understanding an analytics workload, the Cortana Intelligence Suite Process, the foundations of data transfer and storage, data source documentation, storage and processing using various tools.
# About the Course Welcome to the Operationalizing Solutions with Azure Data Factory (ADF), delivered by your Microsoft Data Science team. In this workshop, you’ll cover how ADF can be used to incorporate machine learning into your data workflows. This allows your data to be used for predictive purposes and not just historical reporting. This course is designed to take approximately 2-3 hours. All materials are provided for follow-on self-study. After completing the course, a student should be able to deploy a predictive experiment from Azure ML as an API and schedule Azure Data Factory to call that API in order to make predictions on data. # Prerequisites There are a few things you will need in order to properly follow the course materials: - Experience and an understanding of ADF (similar to what would be covered in the Cortana Intelligence Suite Workshop) - Experience using Azure ML (similar to what would be covered in the Cortana Intelligence Suite Workshop) - A subscription to Microsoft Azure (this may be provided through your company or as part of your invitation – you must have this enabled prior to class – you will be using Azure throughout the course, for all labs, work and exercises) - You can sign up for a free account here (but don’t use it until the class starts, and don’t sign up more than a week in advance of the class) – https://azure.microsoft.com/en-us/pricing/free-trial/ Or you can use your MSDN subscription – https://azure.microsoft.com/en-us/pricing/member-offers/msdn-benefits/ - Your employer may provide Azure resources to you, but make sure you check to see if you can deploy assets and that they know you’ll be using their subscription in the class. It’s also a good idea to have a general level of predictive and classification Statistics, and a basic understanding of Machine Learning. A brief overview of these technologies is covered for the concepts presented. # Agenda What will you learn - This course is self-paced, so the videos and labs can be done at your own pace. In total, the materials should take 2-3 hours. # Skills taught - Sourcing Data from Azure Storage and other locations - Converting an Azure ML experiment into a production-level API - Call machine learning models as part of the ADF pipeline - Storing results to Azure Storage and other locations # Technologies Covered - Cortana Intelligence - Data Factory - Azure Storage - Azure ML - Azure Data Factory # Materials - Video Training Series https://channel9.msdn.com/Series/Operationalizing-Solutions-with-Azure-Data-Factory