Student Policies

A student shall be deemed to be in Good Academic Standing only if they are making appropriate progress towards the degree as defined and communicated by the program.

To be in Good Academic Standing within the MS in Applied Data Science program, students are expected to:

• Maintain a cumulative grade point average of 3.0 or higher
• Complete all required MS in Applied Data Science courses with a B- or higher
• Adhere to high standards of conduct in the classroom
• Adhere to the University’s policies regarding academic honesty and plagiarism
• Be collegial, responsive to peers, and fairly contribute when engaged in group projects and/or team capstones
• Adhere to deadlines and respond to email correspondences sent by University officials

Students are expected to maintain Good Academic Standing and make academic progress toward the degree throughout their graduate career. If a student is deemed not to be in Good Academic Standing, the student may be placed on Academic Probation upon the recommendation of the faculty in their program and approval of the Program Director. Students who decide to take a Leave of Absence while on Academic Probation will remain on Probation status upon resumption of studies. If placed on Academic Probation status, it will only remain until all action items outlined in the letter are completed and the prescribed timeframe of the Academic Probation status has ended.

The MS in Applied Data Science program will regularly assess each student and communicate in writing (1) if a student is not in Good Academic Standing, (2) what must be accomplished to return to Good Academic Standing, (3) in what timeframe it must be achieved, and (4) what the consequences are if the requirements to achieve good academic standing are not completed within the timeframe (e.g., academic probation, dismissal).

For any/all students* enrolled in the MS in Applied Data Science program in Autumn 2022 and beyond, the maximum period between a student’s first enrollment in the program and the student’s degree completion cannot exceed 16 academic quarters (4 years). For any/all students enrolled in the MS in Applied Data Science program prior to Autumn 2022, the student’s degree completion cannot exceed 20 academic quarters (5 years).

With the exception of the Summer quarter, which is self-term activated, students who are not enrolled in any courses by Week 4 for the Autumn, Winter, and Spring quarters will have a hold placed on their account preventing registration in future quarters. To remove the hold, students must meet with their Academic Advisor prior to resuming coursework in the program.

For any student considering not enrolling in courses for more than one quarter, we encourage moving forward with a leave of absence request. Please note that approved leave of absence time or inactive time away from the program still counts towards the maximum time to completion. In rare instances on a case-by-case basis, an exception might be made following review by both the program and the Physical Sciences Division Dean of Students; however, exceptions are not guaranteed.

If a student has been inactive (not enrolled) in the program for a total of one year (4 academic quarters) or longer, the student will be automatically placed on an administrative leave of absence from the MS in Applied Data Science program. Students will be informed of this action by their Academic Advisor and will remain on administrative leave until they reach the maximum of number of academic quarters, for completing the program. Students interested in resuming their coursework while on an administrative leave of absence, must complete the Request to Resume Studies form and meet with their Academic Advisor.

Failure to complete the program within the maximum time to complete will result in the student being administratively dismissed and withdrawn from the MS in Applied Data Science program. Readmission to the program will require a new application based upon the program’s current admission standards. The MS in Applied Data Science program is not obligated to readmit a student. If readmitted, the transfer of existing completed units is not guaranteed and must be evaluated on a case-by-case basis based on the program’s current degree progression standards.

This policy is subject to review and revision. All students will be informed of any changes to this policy.

* Students are defined as any/all individuals enrolled in the full-time or part-time MS in Applied Data Science program – In-Person or Online. MS in Applied Data Science students are allowed to take up to 300 Units per quarter. Students may submit a request to the MS in Applied Data Science Advising Team to take 400 units. Students found to be registered for more than 300 units without MS in Applied Data Science administrative approval will result in additional courses administratively removed from their schedule.

NBC Tower Student Lounge Community Guidelines
The University of Chicago – Cityfront Campus

Respect for Space

• Our Shared Space: This lounge belongs to us all. Cleaning supplies will be provided in the Student Lounge. Keep the lounge clean and tidy. Dispose of trash properly and help maintain a welcoming environment for all.
• Responsible Use: Use the facilities and resources responsibly, ensuring they are available for all members. Engage with them thoughtfully and avoid any actions that could adversely affect others or the space. Avoid any activities that may cause harm, damage, or disturbance to the physical lounge space.
• Noise Consideration: As scholars, we value both lively debates and silent contemplation. Monitor your noise levels, tailoring your activities to the needs of the space and your peers. Keep conversations at a reasonable volume and use designated areas (e.g., reserved study rooms) for group discussions or socializing.
• Personal Belongings: Take responsibility for your personal belongings. Do not leave items unattended, and avoid using excessive space.
• Lost & Found: If you lose or find any items that are left behind in the Student Lounge, please turn them in or seek to find them in the Operations Office, located in NBC Tower Suite 2800.

Respect for Others

• Respect for Peers: This lounge space thrives on mutual support and collaboration. Let’s celebrate the tapestry of backgrounds and experiences that we bring. Treat everyone with kindness, respect, and inclusivity, regardless of their program affiliation or background. Furthermore, respect others’ personal belongings and seek permission before borrowing or moving items.
• Inclusive Language: Let your language reflect the inclusivity and respect we cherish. Please avoid the use of offensive or discriminatory comments, jokes, or language that could make anyone uncomfortable or feel less valued.
• Conflict Resolution: In case of disagreements or conflicts, approach them respectfully and seek amicable resolutions. If things escalate beyond the point of individual parties being able to resolve issues themselves, we encourage you to contact the appropriate program administrators.

Upholding our Standards

Students must adhere to all University of Chicago (e.g., Student Manual), division, and program policies, rules, and regulations while using the lounge. We reserve the right to close and restrict access to the Student Lounge and ask any occupants to leave due to inappropriate behavior and/or violations of conduct outlined in existing policies.

Please report any serious maintenance issues, concerns, or potential violations of any policies or community guidelines to the appropriate program administrators listed below:

• MScTRM & MScBMI: Jarvis Purnell, Interim Director of Student Affairs, at jarvis1@uchicago.edu
• MS in Applied Data Science: DuJuan Smith, Director of Student Affairs, at dusmith@uchicago.edu

You must earn a grade of B- or better in each of the courses that apply toward your degree requirement. All grades received are final. Grades can only be changed by the Registrar due to an administrative error. It is the students’ responsibility to check their records at the end of each quarter and report all grading errors to your MS in Applied Data Science Advisor immediately.

In the MS in Applied Data Science program, we consider grading to be the exclusive purview of the instructor. If concerns remain after a reaching out to the course instructor, students may follow the PSD Student Concerns and Grievance policy.

If a grade below B- is earned for a course, that class will not count towards graduation. If the course is a degree requirement for graduation, the student will need to register and pay for the course to take in again. Tuition and fees will be assessed as scheduled.

MS in Applied Data Science courses are NOT available for auditing purposes. Students must be registered for courses and are subject to tuition and fees.

MS in Applied Data Science students are allowed to take up to 300 Units per quarter. Students may submit a request to the MS in Applied Data Science Advising Team to take 400 units. Students found to be registered for more than 300 units without MS in Applied Data Science administrative approval will result in additional courses administratively removed from their schedule.

A course may have one or more prerequisites for registration. Before registering for any course, a student must first have completed all necessary prerequisites (PQs) or be enrolled in the course prior to registration.  These PQs are essential foundations for student learning and success in the MS in Applied Data Science program.  Students are responsible for being aware of this policy prior to registration each quarter and may not bypass any prerequisites required for a selected course.