Cloud Computing

3 Credits · Level: Graduate, Undergraduate

Prerequisite: MATH 5051 AND MATH 5200 or Equivalents Description: The topics covered in this MS level course are all concerned with analytics and computation involving data sets which may be very large, e.g. big data. The term analytics will refer to modeling and computation within specific mathematical frameworks such as large matrices and other definite file types, and tools that enable measuring, parsing, understanding and visualizing the data. The term big data refers to an analytical context that requires a distributed computing framework for effective processing. The course goals are to learn about advanced computational tools and methods utilized in the data science field. We will learn about how to use and administer cloud computing resources, useful utilities in the linux environment, and the AWS suite of cloud services. Among the AWS services we will focus on general use services (e.g. EC2, S3), but also the Hadoop distributed computing ecosystem (as implemented in AWS EMR), the map reduce framework, and the application of these concepts to working with and understanding large datasets. Prospective students should study the prerequisites listed below that include knowledge of the Linux command line language and some use of Python. This is a hands-on course.