About this course
This course is part of the Microsoft Professional Program Certificate in Data Science and Microsoft Professional Program in Artificial Intelligence.
Machine learning uses computers to run predictive models that learn from existing data in order to forecast future behaviors, outcomes, and trends.
In this data science course, you will be given clear explanations of machine learning theory combined with practical scenarios and hands-on experience building, validating, and deploying machine learning models. You will learn how to build and derive insights from these models using R, Python, and Azure Machine Learning.
Meet the instructors
Senior Content Developer
Microsoft Learning Experiences
Graeme has been a trainer, consultant, and author for longer than he cares to remember, specializing in SQL Server and the Microsoft data platform. He is a Microsoft Certified Solutions Expert for the SQL Server Data Platform and Business Intelligence. After years of working with Microsoft as a partner and vendor, he now works in the Microsoft Learning Experiences team as a senior content developer, where he plans and creates content for developers and data professionals who want to get the best out of Microsoft technologies.
Dr. Steve Elston
Quantia Analytics, LLC
Steve is a big data geek and data scientist, with over two decades of experience using R and S/SPLUS for predictive analytics and machine learning. He holds a PhD degree in Geophysics from Princeton University, and has led multi-national data science teams across various companies
MIT and Duke
Cynthia leads the Prediction Analysis Lab at MIT, and is associated with the Computer Science and Artificial Intelligence Laboratory and the Sloan School of Management. She holds a PhD in applied and computational mathematics from Princeton University, and was previously, an associate research scientist at the Center for Computational Learning Systems at Columbia U.