Computing for Data Science

Catalog description

Provides students with hands-on experience of understanding the challenges in analyzing big data. Introduces a Linux-based environment for data scientists. A variety of topics are covered, including database management and manipulation, computation resource management, parallel computing and GPU-based computation. This is an object-oriented course, with students collaboratively working on projects using shared resources. By running the computations on a cloud platform, students gain valuable first-hand experience of working in a computational environment. The course is primarily divided into four modules including Linux environment, Data manipulation, SQL database, and R module. Prerequisite(s): DATS 7510 >= C Lecture Hours: 3 Repeatability: May not be repeated for credit. Grade Mode: Normal, Audit Program Restrictions: DPHIL_BIOS, MS_BIOS, MS_DSCI Campus Restrictions: AU Online Schedule Type (Primary): Asynchronous Instruction Click here for the Schedule of Classes.