Registration - Bachelor of Science in Information Science at Shady Grove (InfoSci)

UMD iSchool courses use the program codes INFM, INST, and LBSC. In order to be eligible for registration, students must have their financial accounts settled and have no holds on their account. Please note that Student Services does not have access to your student bill or holds. All questions about your student billing account and holds must be directed to the Student Financial Services and Cashiering.

The following is our standard Fall 2020 cohort schedule (you will follow this schedule unless it is otherwise stated by your academic advisor during your mandatory advising appointment this summer):

Course Number Course Name Course Section Date
INST301 Introduction to Information Science ESG1 Online
INST311 Information Organization ESG1 W 9:00-11:45am
INST314 Statistics for Information Science ESG1 Tu,Th 8:00-9:15am
INST326 Object-Oriented Programming for Information Science ESG1 Tu,Th 9:30-10:45am
INST335 Organizations, Management and Teamwork ESG1 M 8:00-10:45am

  1. Review Your Pre-Set Class Schedule
    Students in this program will receive a pre-set class schedule that allows for the completion of the program in two years. You will be provided with this schedule by your advisor prior to registration.
     
  2. Ready to register?
    Consult the University Schedule of Classes and register for undergraduate and graduate classes through Testudo, the University of Maryland registration portal.
  1. Non-InfoSci majors will be unable to register for INST courses until the first day of Schedule Adjustment, and may only enroll in INST courses with permission from the instructor of the course.
     
  2. The instructor must e-mail the Undergraduate Student Services Office directly.

    * This process does NOT guarantee permission to enroll. Permission may be granted pending the availability of seats in the course.

The following resources can help you to prepare for the courses you will be taking in the InfoSci program.

Python:

R:

  • “Statistics (The Easier Way) with R: an informal text on applied statistics” by N.M. Radziwill ISBN13 - 9780996916059
  • Datacamp.com
  • Codecademy.com

 

 

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