DATA-150. R for Data Science

This course will provide a hands-on overview of the statistical programming language R with data science applications in mind. A course project will involve analysis of Common Intellectual Experience texts using R, giving students a unique way to reflect upon their growth and progress through the Ursinus core curriculum. Students will define a problem; collect unstructured data; clean the data; and transform the data into information, the information into knowledge, and the knowledge into wisdom in connection with the core curriculum. Three hours per week. Prerequisites: CIE-200 and STAT-141Q or –243W or permission of instructor. Four semester hours.

DATA-201. Data Analytics

A broad introduction to the field of data analytics. The course focuses on the proper deployment and use of data analytic tools and techniques that are successfully utilized by modern organizations. Students will be introduced two programming language: SQL and R. After taking the course, students will demonstrate a mastery of SQL queries to extract data from a relational database; demonstrate the ability to manipulate, analyze and visualize data; and demonstrate the ability to utilize statistical scripting languages and software tools to analyze data for insights. Three hours per week. Prerequisites: STAT-141Q, DATA-150 (or another approved course in R programming), CS-170 (or another approved course in Python programming). Four semester hours.

DATA-202. Data Care and Cleaning

Building upon foundational analytics tools and techniques, this course further explores advanced data pre-processing tools used in the field of data analytics. Students will focus on data care, data cleaning and data visualization with Python. By the end of this course students will master modern data pre-processing libraries in Python. Prerequisite: CS-170 (or another course in Python programming). Three hours per week. Four semester hours.

DATA-301. Data-Driven Insights and Society

An introduction to the methods used to build and manage databases, the storehouses of information used by organizations to understand their operations and make decisions. Students who successfully complete the courses will know how to choose appropriate tools for a given data management application; understand relations in the context of databases; construct distributed databases and NoSQL databases; and develop a substantial data management project. Prerequisites: DATA-201 and 202. Three hours per week.Four semester hours.

DATA-350. Topics in Data Analytics

An occasional course focusing on a special topic in data analytics. Prerequisites will vary. Three hours per week.Four semester hours.