Data Science

Curriculum and Specialization Details

The Master's in Data Science requires the successful completion of 12 courses to obtain a degree. These requirements cover six core courses, a leadership or project management course, two required courses corresponding to a declared specialization, two electives, and a capstone project (498) or thesis (590). A specialization should be declared as part of the application process. Students who already have experience in one area of specialization may forgo a specialization and take four electives. Current students should refer to curriculum requirements in place at time of entry into the program.

Analytics and Modeling Specialization

In the world of data science, the analysts and modelers specialize in testing real-world predictions about data. Data analysts and modelers conduct research and take complex factors into account to build predictive models and create forecasts upon which data-driven decisions can be made. This specialization prepares data scientists to utilize statistical algorithms, predictive modeling, data mining, and machine learning approaches to determine the likelihood of future outcomes based on collected data and data trends.

  • MSDS 410-DL Regression Analysis and Multivariate Methods
  • MSDS 411-DL Generalized Linear Models

Data Engineering Specialization

After analysts and modelers have built and tested models, data engineers implement models to scale within an information infrastructure, creating systems and workflows to organize and manage large quantities of data. This means understanding computer systems (including software, hardware, data collection, and data processes) and solving problems related to data collection, security, and organization. This specialization trains data scientists to utilize system-wide problem-solving skills, choose hardware systems, and build software systems for implementing models made by data analysts to scale in productions systems.

  • MSDS 432-DL Foundations of Data Engineering
  • MSDS 434-DL Analytics Application Development

Analytics Management Specialization

As the strategic and tactical decisions of organizations become increasingly data-driven, analytics managers managers bridge the work of analysts and modelers with business operations and strategy to lead data science teams, address future business needs, identify business opportunities, and translate the work of data scientists into language that business management understands. This specialization equips data scientists with the communication and management strategies needed to be data-driven leaders who utilize models, analyses, and statistical data to improve business performance.

  • MSDS 474-DL Accounting and Finance for Analytics Managers
  • Either MSDS 475-DL Project Management or MSDS 480-DL Business Leadership and Communications*

*Students in this specialization are required to take both MSDS 475-DL and MSDS 480-DL to complete the program.

General Track

Students' seeking a less prescriptive curriculum may tailor electives coursework to their specific professional needs. This will be particularly useful for data scientists seeking employment with small businesses and smaller-scale projects, in which a single data scientist might have to serve the functions of data analyst, data engineer, and analytics manager simultaneously. Instead of two required courses and two electives, students choosing no specialization will instead take four electives.

About the Final Project

Students may pursue their capstone experience independently or as part of a team. As their final course, students take either the individual research project in an independent study format or the classroom final project class in which students integrate the knowledge they have gained in the core curriculum in a project presented by the instructor. In both cases, students are guided by faculty in exploring the body of knowledge on predictive analytics while contributing research of practical value to the field. The capstone independent project and capstone class project count as one unit of credit.

  • MSDS 498-DL Capstone Project or
  • MSDS 590-DL Thesis Research