The main purpose of the course is to give students the ability to analyze and present data by using Azure Machine Learning, and to provide an introduction to the use of machine learning with big data tools such as HDInsight and R Services.
In addition to their professional experience, students who attend this course should have programming experience using R, and familiarity with common R packages. Students should have knowledge of common statistical methods and data analysis best practices. Basic knowledge of the Microsoft Windows operating system and its core functionality and working knowledge of relational databases is also required.
5 Days/Lecture & Lab
The primary audience for this course is people who wish to analyze and present data by using Azure Machine Learning. The secondary audience is IT professionals, developers, and information workers who need to support solutions based on Azure machine learning.
Introduction to Machine Learning
- Introduction to Azure Machine Learning
- Managing Datasets
- Preparing Data for use with Azure Machine Learning
- Using Feature Engineering and Selection
- Building Azure Machine Learning Models
- Using Classification and Clustering with Azure machine learning models
- Using R and Python with Azure Machine Learning
- Initializing and Optimizing Machine Learning Models
- Using Azure Machine Learning Models
- Using Cognitive Services
- Using Machine Learning with HDInsight
- Using R Services with Machine Learning