Offers students an opportunity to learn a hands-on approach to understanding how large-scale data sets are processed and how data science algorithms are adopted in the industry through case studies and labs. This project-based course builds on INFO 7390 and focuses on enabling students with tools and frameworks primarily to build end-to-end applications. The course is divided into three parts: building the data pipeline for data science, implementing data science algorithms, and scaling and deploying data science algorithms
The ability to use python is part of the grade. Students must demonstrate ability to setup data for learning, train, test, and evaluation using either python or R, but all assignment examples and solutions will be presented in python. The assignments include paper exercises designed to reinforce conceptual understanding. Quizzes and exams. A term project is required. A portfolio blog is required.