The CADS curriculum will consist of 9 credits of data science coursework and a 3-credit practicum as outlined below:

Program Path

Students beginning in the Spring will take three semesters of coursework: Spring 1 INLS 761 and 774, Fall INLS 773, 775, and 772, Spring 2 INLS 792 (Practicum)

Students beginning in the Fall will take four semesters of coursework: Fall 1 INLS 773 and 775, Spring 1 INLS 761 and 774, Fall 2 INLS 772, Spring 2 INLS 792 (Practicum)

This program is designed to be completed in consecutive semesters. If you need to take a semester off please emails

Course Descriptions

Data Analysis
This course provides fundamental skills for developing software for the analysis of structured data sets. Students will learn data analysis techniques using numeric, textual, and tabular data in the context of data science topics such as information retrieval, textual analysis, and basic machine learning. 

Applied Statistics, Machine Learning and Data Communication
An applied course introducing computational statistical analysis, machine learning, data exploration and communication with a focus on applied concepts as encountered within common data science applications.

Databases for Data Science
Overview of the design and implementation of database systems, focusing on applied topics most relevant to the practice of data science.

Applied Data Ethics
Introduction to ethical issues faced by data scientists in creation, collection, curation, and use of data at multiple scales.

Applied Data Curation and Management 
Introduction to digital and data curation in a wide array of environments including business, government, and academia. 

Applied Data Science Practicum
Builds upon the formal classroom instruction in data science concepts and technologies through a "hands-on" project experience within an industry, non-profit, or other work environment that relates the student's primary field of study/practice.