Academic Regulations for the Master of Science in Computer Science

M.S. Program Overview  | Admissions Requirements


Resident Study Requirements

The total number of hours of academic credit used to satisfy degree requirements consists of all course credit hours that appear on the plan of study, other graduate course credit hours with grades of C or better that appear on the IUPUI/Purdue transcript and research hours that appear on the IUPUI/Purdue transcript. For a Master of Science in Computer Science at IUPUI, at least one-half of the total credit hours used to satisfy degree requirements must be earned in residence on the IUPUI campus. Transfer credits used to satisfy degree requirements must also appear on the plan of study. Course credits obtained via televised instruction from a campus shall be considered to have been obtained in residence on that campus. At least 30 total credit hours of 500 level or above courses are required. In fulfilling these requirements, a maximum of 15 credit hours will be allowed from any one semester (total 15 for summer I and II combined).

Transfer Credit

Credits earned for graduate study at other universities may be applied toward the Master of Science in Computer Science with the approval of the Advisory Committee, the Graduate Committee and the Graduate School. Such credits may not have been used to meet other degree requirements. Transfer credits are normally limited to six semester-hours. Application for the transfer of credit is made when the plan of study is presented for approval. This should be done as soon as possible. Only credit hours associated with graduate courses for which grades of B or better were obtained will be eligible for transfer.

Non-departmental Courses

Non-departmental courses are limited to 3 credits (1 course) for course-only students, selected from the pre-approved list below.

  • INFO-B 535: Clinical Information Systems
  • INFO-I 501: Introduction to Informatics
  • INFO-H 516: Applied Cloud Computing for Data Intensive Sciences
  • INFO-H 559: Media & Technology Entrepreneurship (Previously INFO-H 550: Legal and Business Issues in Informatics)
  • INFO-I 590: Topics in Informatics: Legal and Social Informatics of Security
  • INFO-B 642: Clinical Decision Support Systems
  • INFO-I 643: Natural Language Processing for Biomedical Records and Reports
  • LIS-S 634: Metadata
  • MATH 51100: Linear Algebra with Applications
  • MATH 52200: Qualitative Theory of Differential Equations
  • MATH 53700: Applied Mathematics for Scientists and Engineers I
  • OLS 58100: Workshop in OLS: Critical Thinking & Problem Solving
  • PHYS 59000: Reading & Research
  • STAT 52900: Applied Decision Theory and Bayesian Analysis

Up to 3 additional credits (for a total of 6) may be allowed for M.S. Thesis or M.S. Project students for courses related to research area; prior approval of the Advisory and Graduate Committees are required for registration.

Graduate Nondegree Credit Hours

A maximum of 12 credit hours (500 level or above) earned prior to admission to the M.S. in Computer Science Program can be listed on the Plan of Study.

Major Professor

Every student in the M.S. in Computer Science Program is required to select a major professor who acts as the chair of the Advisory Committee and who agrees to supervise the student's graduate study, research/project, and writing. The major professor/student relationship must be a mutually acceptable one.

Assessment

General Academic Standards Grades of A and B are expected; a maximum of 6 credit hours of C or C+ may be included provided an overall grade average of 3.0 (B) is maintained. Other grades are unacceptable and the course work will not be counted toward fulfilling program requirements as listed on the student's plan of study.

Overall Student Performance

The objective of this type of assessment is to determine whether or not a given student is satisfactorily progressing towards, and finally achieves, the performance objectives that the Graduate Faculty has set for the Program.

  • The instructor in each class will evaluate the progress of each student through the course and the final achievement by using the mechanisms and objectives stated in the course syllabus. These vary by course. The mechanisms are typically evaluations of exercises, written and oral examinations, and projects, collaboratively or individually executed. The general outcomes are that the student will understand the theoretical concepts and be proficient in applying them within the context of the course's subject.
  • The student must accumulate individual and cumulative performance ratings for all courses taken that satisfy the minimum acceptable standards the department establishes. The outcome here is that the graduate will have a uniformly high technical capability across a broad spectrum of subjects in computer science.
  • Each student must demonstrate satisfactory accomplishment in a fundamental domain of knowledge, which the group of Core Courses provides. The outcome of this requirement is that the student will possess solid knowledge of the theoretical bases of computer science.
  • Every student must achieve sufficiently deep command of a specialization area to successfully complete a thesis or project. The evaluations from the specialization courses combined with the evaluation by the student's thesis or project supervisors measure this. The outcome of the student's preparation for this will be that she or he will possess expertise in a specific research or application area for future use in the profession.
  • Finally, each student must make a written and public presentation of the thesis or project work, which the student's Examination Committee evaluates. This measures and sets a minimum standard on the student's capability to:
    • integrate appropriately new knowledge with the knowledge and skills presented in the taken courses in ways sufficient to engage in research or the solution of problems arising in practice,
    • communicate effectively, orally and in writing, with colleagues or team mates while solving problems and in presenting the solutions,
    • think analytically and critically and apply a variety of logical and computational tools as aids in this process,
    • articulate the relationships between the area of expertise and other discipline areas and society in general.