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Data Science and Analytics

MS in Data Science and Analytics

Bradley University offers an interdisciplinary graduate program leading to the degree of master of science in Data Science and Analytics. This course of study is designed to prepare students for professional careers in the field or for further study and research.

The Data Science and Analytics graduate program provides students with the necessary skills to effectively use large data sets to solve problems and potentially find new insights. 

Students can concentrate their study in various application areas including: 1) business analytics, 2) computational data science, and 3) engineering analytics.

In addition to satisfying all the Graduate Education requirements for the degree, all candidates for the master’s degree must satisfy the following departmental requirements:

  • At least 34 hours of graduate-level coursework. Some remedial course(s), e.g., an introductory programming class, such as CS 502, or an entry level statistics course, such as MTH 111, Q M 262, or IME 302, do not count as part of the total hours needed.
  • No "D" grades can be counted in the completion of requirements for the degree.
  • Every student must pass a written comprehensive examination that will be based on the core requirements for the program pursued.

Students in the Data Science and Analytics program may register for only three courses per semester. Any exceptions must be approved by the appropriate department chair.

Admission requirements to the Data Science and Analytics program are given below:

  • completed at least one semester of statistics.
  • must submit GRE General Test or GMAT scores taken within the last five years. The applicant may request a GRE or GMAT waiver under certain circumstances.

Note that prospective students who do not meet the conditions for admission may be admitted conditionally, in which case the department will prescribe a program for the removal of such admission conditions. Conditional status must be removed prior to graduation.

Data Science and Analytics

In addition to meeting all the general requirements of Graduate Education and of the department(s) as stated above, candidates for the master’s degree in Data Science and Analytics must satisfy the following requirements:

  1. At least 24 of the 34 required hours must be earned in courses labeled CS, CIS, IME, or MIS.
  2. To satisfy the core (breadth) requirement, six courses or 16 credit hours must be taken:
    • IME 511 Probability & Statistics for Analytics (3 credit hours)
    • IME 512 Regression and Experimental Design (3 credit hours)
    • CS 560 Fundamentals of Data Science (3 credit hours)
    • CS 571 Database Management Systems (3 credit hours) or IME 514 Operations Research (3 credit hours)
    • MIS 570 Introduction to Business Analytics (3 credit hours)
    • BUS 511 Communicating Quantitative Information (1 credit hour)
  3.  To satisfy depth requirements, the student must take three or four courses from one of the concentrations offered and listed below. No course taken to satisfy the core requirement (item 2 above) may be counted as one of the courses in this requirement. The Business Analytics concentration is 9 credit hours, the Computational Data Science concentration is 12 credit hours or 15 credit hours if a student writes a thesis, and the Engineering Analytics concentration is 9 credit hours.
  4. The remaining credit hours will be made-up of approved elective courses.

For admission into the data science and analytics program, a student must have the approval of the department(s) and have completed: 

  1. at least one semester of statistics,
  2. submitted standardized test results, and 
  3. specific requirements for one of the concentrations
    1. Business Analytics concentration:
      1. basic spreadsheet proficiency
    2. Computational Data Science concentration: 
      1. Two semesters of programming classes or CS 502
      2. Two semesters of calculus
      3. Linear Algebra
    3. Engineering Analytics concentration
      1. One semester of programming class or numerical analysis
      2. Two semesters of calculus
      3. Linear Algebra

Concentrations

Business Analytics Concentration - 9 credit hours (ch)

The Business Analytics concentration provides students with the necessary skills to analyze organizational data to aid in business decision-making. The concentration is comprised of 9 semester hours of study.

Prerequisites:

  • Basic spreadsheet proficiency

Required courses (3 courses):

  1. MIS 571 Business Analytics Software and Applications I - 3 ch
  2. MIS 573 Data Visualization for Business - 3 ch
  3. MIS 590 Business Analytics Consulting Project – 3 ch OR CS 594 Capstone Project for Data Science - 3 ch OR IME 691 Research/Practicum – 3 ch 

Computational Data Science Concentration - 12-15 credit hours (ch)

The Computational Data Science concentration provides students with the necessary skills to understand the theory and algorithms utilized in data science and to be able to implement and apply them. The concentration is comprised of 12 to 15 semester hours of study.

Prerequisites

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

Required courses (4 courses):

  1. CS 562 Machine Learning - 3 ch
  2. CS 563 Knowledge Discovery and Data Mining - 3 ch
  3. CS 572 Distributed Databases and Big Data - 3 ch
  4. CS 594 Capstone Project for Data Science - 3 ch OR CS 699 Thesis – 6 ch (Note: 3 ch taken for two consecutive semesters) OR MIS 590 Business Analytics Consulting Project – 3 ch OR IME 691 Research/Practicum – 3 ch 

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.

Engineering Analytics Concentration - 9 credit hours (ch)

The Engineering Analytics concentration provides students with the skills to analyze and process large-size and complex data, to utilize proper methodology in identifying problems, formulating mathematical or algorithmic models, and to solve problems arising from engineering applications, including product design, process design, manufacturing execution, inventory management, production planning, quality control, economic analysis of engineering decision.

Prerequisites

  • One semester of programming class or numerical analysis
  • Two semesters of calculus
  • Linear algebra

Required Courses (3 courses):

  1. IME 568 Engineering Analytics I - 3 ch
  2. IME 586 Logistics and Supply Chain Systems - 3 ch
  3. IME 691 Research/Practicum – 3 ch OR MIS 590 Business Analytics Consulting Project – 3 ch OR CS 594 Capstone Project for Data Science - 3 ch

Possible electives for the Data Science and Analytics Program include courses required by the other concentrations, or additional courses listed below, or courses approved by the department chair. It is the responsibility of the student to ensure they have met the prerequisites for their elective courses. 

  • CIS 576 Data Management
  • CIS 580 Digital Society and Computer Law
  • CS 541 Python for Data Science
  • CS 561 Artificial Intelligence
  • ECE 565 Engineering Applications of Machine Learning
  • IME 501 Engineering Cost Analysis
  • IME 526 Reliability Engineering
  • IME 561 Simulation of Manufacturing & Service Systems
  • IME 578 Engineering Analytics II
  • IME 583 Production Planning and Control
  • MIS 613 Advanced Algorithms for Business
  • MTG 624 Marketing Decision Making
  • MTH 510 Numerical Methods I
  • MTH 511 Numerical Methods II

This is the official catalog for the 2021-2022 academic year. This catalog serves as a contract between a student and Bradley University. Should changes in a program of study become necessary prior to the next academic year every effort will be made to keep students advised of any such changes via the Dean of the College or Chair of the Department concerned, the Registrar's Office, u.Achieve degree audit system, and the Schedule of Classes. It is the responsibility of each student to be aware of the current program and graduation requirements for particular degree programs.