Degree Requirements for the M.S. in Applied Data Science

Degree Requirements

The plan of study is 30 credit hours. It includes six core courses and four elective courses. Transfer students may be able to transfer in approved graduate courses from an accredited institution.

F-1 students can only take one online course per semester. They must take a minimum of 8 credit hours per semester; the exception being in their final semester. These limitations apply to fall and spring semesters but not summer sessions.

Core Courses (18 cr.)

Students may test out of INFO-H 611 and LIS-S 511. Students do not receive credit toward their required 30 credit hours by testing out of a course. However, they may instead replace the course with a specialization course or approved elective.

Elective Courses (12 cr.)

Students may replace elective courses with non-Luddy courses with the permission of the program director.

Thesis or Project

The Thesis/Project is available to highly motivated students ready to carry out publishable research. Students must prepare a prospectus and gain a commitment from a primary faculty advisor with research interests in data science by the end of the first semester. By the end of the second semester, students must complete a course on research design and methods (e.g., INFO-I 575 or LIS-S 506).

The thesis or project must be completed in two semesters or in a semester and summer. Thesis students register for a total of 6 credits and project students register for a total of 3–6 credits of INFO-H 695 Thesis/Project in Data Science. Students are required to prepare and defend a research proposal with a timeline of deliverables in addition to the thesis or project.

The following approved electives are available in the fall and spring semesters.

Note: Applied Data Science MS students may take up to nine Computer Science credits to count towards their degree program. ADS Program Director permission must be given to take more than nine credits. Verify with the course professor that you have the necessary background and prerequisites before enrolling in a Computer Science course.

Substitute courses accommodate special interests and scheduling needs, such as for an online course. A substitute course satisfies the core or specialization course requirement.

A student wishing to substitute a course or take an elective course from our Data Science program in Bloomington must apply for graduate non-degree status at least one month before the start of the semester.

  • INFO-H 510
    • INFO-B 518 Applied Statistical Methods for Biomedical Informatics
    • PBHL-B 561 Introduction to Biostatistics I (Accelerated students only)
  • INFO-H 515
    • CSCI-B 555 Machine Learning
    • INFO-B 518 Applied Statistical Methods for Biomedical Informatics
    • INFO-I 526 Applied Machine Learning (IUB)
  • INFO-H 517
    • CSCI-P 583 Data Visualization
  • INFO-H 518
    • CSCI-P 558 Deep Learning
  • INFO-H 519
    • CSCI-B 651 Natural Language Processing
    • INFO-B 643 Natural Language Processing for Biomedical Records and Reports
  • INFO-I 575
    • LIS-S 506 Introduction to Research
  • LIS-S 511
    • CSCI-B 561 Advanced Database Concepts
    • INFO-B 512 Scientific and Clinical Data Management
  • NEWM-N 510
    • LIS-S 517 Web Programming

Degree Maps

Fall Year 1

Spring Year 1

Summer

  • ADS specialization course

Fall Year 2

Spring Year 1

Summer Year 1 (optional)

  • ADS specialization course

Fall Year 1

Spring Year 2