Throughout society, large and complex digital data has become ubiquitous in science and engineering — it has the potential to solve problems, gain knowledge and make decisions in new ways. The field of data science draws on elements of computer science, statistics and interdisciplinary applications to address the unique needs of gaining knowledge and insight through data analysis. Data science skills open doors to almost any field such as applications in the physical processes and the environment, additive manufacturing, health care, economics and e-commerce. Students will draw on the rich academic and professional resources at Mines through a program that is unique and well-suited for training a future cadre of data scientists and data engineers.

This non-thesis master’s program gives students a foundation in statistics and computer science, while also providing knowledge in a particular application domain of science or engineering. This program follows a 3×3 + 1 design: three modules each consisting of three, 3-credit courses, and a mini-module (three credit hours) devoted to professional skills and enrichment (see the classes here). The balance between these elements is a strength of the program and prepares students for data science careers in industry, government or for further study at the PhD level. Moreover, the application coursework can be flexible and tailored to each student. Training future data scientists in an interdisciplinary fashion unlocks skills that solve problems and gain knowledge in new ways through data-driven discovery and data-supported decision making.  This program allows students to either increase their ability in data analytics while developing a focused area of application or to alternatively allow a student with depth in one area of application to gain skills in statistics and computer science.