Master Of Science In Data Science And Analytics - Computational Data Science Concentration

Bradley's 34-hour data science and analytics graduate program teaches you the skills to analyze and process large and complex data. With our computational data science concentration, you'll learn the theory and algorithms needed to collect and understand data properties, build models, identify trends, solve problems and potentially find new insights.

Preparing You For Success

The growing use of electronic media has propelled data mining and knowledge discovery (DM/KD) techniques to the forefront of emerging technologies, increasing the need for experts to analyze and understand the massive amounts of data generated daily.

Bradley's computational data science courses take you through the discovery process and life cycle of a data mining project. You’ll grasp various machine learning algorithms and how to deploy them to analyze data, build forecasting and classification models, or perform unsupervised learning tasks.

By the time you graduate, your experiences may include:

  • Working on real-world, industrial problems assigned as projects in your classes
  • Learning statistical methods for testing and evaluation of models
  • The ability to create helpful and accurate data visualizations
  • Mastering programming languages, such as Python and R, to perform tasks
  • A semester-long capstone research project
  • Writing an optional master's thesis
  • Contributing to research publications

Making Your Mark

Bradley's graduate computational data science program prepares you to develop and apply tools that support the ever-changing data needs of today and tomorrow. You'll graduate with the essential background, knowledge and skills necessary to work as a data scientist or pursue a Ph.D. With applications in virtually every area of engineering, science, medicine, business and education, the techniques you learn are critical to economic management, wealth creation in commerce, and overall improvement of our lives and well-being.

Graduate Program Requirements

Required Courses - 12-15 hrs.

  • CS 562 Machine Learning - 3 hrs.
  • CS 563 Knowledge Discovery and Data Mining - 3 hrs.
  • CS 572 Distributed Databases and Big Data - 3 hrs.
  • CS 594 Capstone Project for Data Science - 3 hrs.
    or CS 699 Thesis - 6 hrs.
    or MIS 590 Business Analytics Consulting Project - 3hrs.
    or IME 691 Research/Practicum - 3 hrs.

Prerequisites

  • Two semesters of programming classes or CS 502
  • Two semesters of calculus
  • Linear Algebra

Interested and qualified students pursuing the Computational Data Science concentration have the option to write a master’s thesis. Students selecting this option are encouraged to choose an advisor and topic as early as possible in order to plan the thesis development and any needed supporting coursework. The following policies apply to theses:

  • A minimum grade point average of 3.5 in computer science and computer information systems graduate courses is required for students enrolling in a thesis course, i.e., CS 699.
  • No student may register for a thesis until 9 hours of graduate courses have been completed in the program.
  • Six credit hours of a thesis course are required and, upon completion, the thesis must be defended in an oral examination.
  • No grade will be given for a thesis course until after the oral defense.
  • A written outline of the thesis project and a tentative schedule must be submitted to and approved by the graduate coordinator and the chair prior to the registration for a thesis course.