TOOLS AND MODELS FOR DATA SCIENCE

Credit Hours: 3 · Undergraduate Upper-Level

This course is an introduction to modern data science. Data science is the study of how to extract actionable, non-trivial knowledge from data. The proposed course will focus both on the software tools used by practitioners of modern data science, as well as the mathematical and statistical models that are employed in conjunction with such software tools. On the tools side, we will cover the basics of relational database systems, as well as modern systems for distributed computing based on MapReduce. On the models side, the course will cover standard supervised and unsupervised models for data analysis and pattern discovery. Can be taken concurrently with COMP 215 . Graduate/Undergraduate Equivalency: COMP 543 . Mutually Exclusive: Cannot register for COMP 330 if student has credit for COMP 543 / DSCI 302 .