This course shows you how to build a model using Amazon Machine Learning (Amazon ML) and use it to make predictions. AWS expert Dan Moore covers the basic types of machine learning, how to prepare your data, and how to make your data available to the Amazon Machine Learning processes. You'll also learn about evaluating a model for accuracy, using it both for batch and real-time predictions, and using tags to manage environments. Designed for developers and technical marketers new to machine learning and for data scientists interested in using the AWS Amazon ML platform, the course provides hands-on experience building a working predictive model using real data. Learners should obtain an AWS account (free from Amazon) and a basic understanding of AWS concepts before beginning the course.

• Understand how to prepare data for use with Amazon ML and how to navigate the console
• Learn how to make real-time and batch predictions using Python and the Amazon Machine Learning console
• Become familiar with advanced machine learning system management concepts like tagging and the model life cycle
• Develop an awareness of model accuracy and learn to use tools for evaluating and comparing accuracy

Dan Moore runs Boulder, Colorado based Moore Consulting, where he builds Amazon Machine Learning models for purposes such as predicting real estate valuations and estimating equipment utilization. Dan is an Amazon Web Services (AWS) trainer who has worked with AWS since 2008. He holds AWS certifications as a Solutions Architect, AWS Certified Developer, and SysOps Administrator.