User Experience Design specialization

Learn not only what users do, but why

Students enrolled in our school at IU’s Indianapolis campus learn methods of data mining, ways to transform large data sets into usable knowledge, and how to represent information visually. The Master of Science in Applied Data Science with a specialization in User Experience Design teaches students the latest methods of data management, analysis, and high-throughput data storage.

The plan of study is 30 credit hours. It includes eight core courses, one specialization course, and one elective course. 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 credits)

  • DSCI-D 501 Introduction to Data Science Programming (was INFO-H 501)
  • LIS-S 511 Database Design
  • DSCI-D 510 Statistics for Data Science (was INFO-H 510)
  • DSCI-D 515 Statistical Learning (was INFO-H 515) (Prerequisite: Graduate Statistics course)
  • DSCI-D 516 Cloud Computing for Data Science (was INFO-H 516) (Prerequisites: Graduate Database course)
  • DSCI-D 518 Deep Learning Neural Networks (was INFO-H 518)

Students may test out of LIS-S 511 Database Design. 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 an approved elective.

UX design core courses (6 credits)

  • INFO-H 541 Interaction Design Practice
  • INFO-H 543 Interaction Design Methods

UX design specialization course (Pick one, 3 credits)

  • DSCI-D 517 Visualization Design, Analysis, and Evaluation (was INFO-H 517) (Prerequisite: Programming experience)
  • INFO-H 561 Meaning and Form in HCI
  • INFO-H 563 Psychology of HCI
  • INFO-H 564 Prototyping Interactive Systems

Elective courses (3 credits)

  • INFO-B 505 Informatics Project Management
  • DSCI-D 517 Visualization Design, Analysis, and Evaluation (was INFO-H 517) (Prerequisite: Programming experience)
  • DSCI-D 519 Natural Language Processing with Deep Learning (was INFO-H 519)
  • INFO-I 575 Informatics Research Design
  • INFO-I 595 Professional Internship
  • INFO-I 698 Research in Informatics (Independent Study)
  • DSCI-D 502 Modeling Crisis (was INFO-P 502)
  • NEWM-N 510 Web Database Development
  • Other approved Applied Data Science electives

Fall Year 1

  • DSCI-D 501 Introduction to Data Science Programming (was INFO-H 501)
  • INFO-H 541 Interaction Design Practice
  • Choose one:
    • DSCI-D 308 Database Design (was INFO-I 308)
    • DSCI-D 510 Statistics for Data Science (was INFO-H 510)

Spring Year 1

  • Choose one:
    • DSCI-D 308 Database Design (was INFO-I 308)
    • DSCI-D 510 Statistics for Data Science (was INFO-H 510)
  • Choose one (must meet prerequisite):
    • DSCI-D 515 Statistical Learning (was INFO-H 515)
    • DSCI-D 516 Cloud Computing for Data Science (was INFO-H 516)
    • INFO-H 543 Interaction Design Methods

Summer Year 1 (Optional)

  • UX Design Specialization or Elective Course

Fall Year 2

  • Choose one (must meet prerequisite):
    • DSCI-D 515 Statistical Learning (was INFO-H 515)
    • DSCI-D 516 Cloud Computing for Data Science (was INFO-H 516)
  • UX Design Specialization Course
  • UX Design Elective Course
  • UX Design Elective Course (If not taken in Summer)

Spring Year 1

  • DSCI-D 501 Introduction to Data Science Programming (was INFO-H 501)
  • INFO-H 541 Interaction Design Practice
  • Choose one:
    • DSCI-D 308 Database Design (was INFO-I 308)
    • DSCI-D 510 Statistics for Data Science (was INFO-H 510)

Summer Year 1 (Optional)

  • UX Design Specialization or Elective Course

Fall Year 1

  • Choose one:
    • DSCI-D 308 Database Design (was INFO-I 308)
    • DSCI-D 510 Statistics for Data Science (was INFO-H 510)
  • Choose one (must meet prerequisite):
    • DSCI-D 515 Statistical Learning (was INFO-H 515)
    • DSCI-D 516 Cloud Computing for Data Science (was INFO-H 516)
    • INFO-H 543 Interaction Design Methods

Spring Year 2

  • Choose one (must meet prerequisite):
    • DSCI-D 515 Statistical Learning (was INFO-H 515)
    • DSCI-D 516 Cloud Computing for Data Science (was INFO-H 516)
  • UX Design Specialization Course
  • UX Design Elective Course
  • UX Design Elective Course (If not taken in Summer)

UX research and other data science careers

  • Application design architect
  • Business technology analyst
  • Data scientist
  • Human factors specialist
  • Information architect
  • Interactive media designer
  • Product analyst
  • Software developer
  • Usability engineer
  • UX researcher
  • Web developer