Undergraduate Minor in Digital Studies

Undergraduate students in the College of the University of Chicago may undertake a minor in Digital Studies as a complement to their primary field of study. This minor is intended not just for students who are majoring in the humanities or social sciences. It may also be of interest to students majoring in the physical or biological sciences who wish to acquire computational skills in the context of linguistic, cultural, and historical studies.

Students who elect to do the minor in Digital Studies must meet with the Associate Director of Curriculum and Instruction of the Forum for Digital Culture before the end of the Spring Quarter of their third year to declare their intention to complete the minor. Students must complete a Consent to Complete a Minor Program form with the assistance of their College advisor and submit this to the Director of Curriculum and Instruction for approval.

Requirements

Students must take six courses to complete the undergraduate minor in Digital Studies, as specified below. Students who have taken courses in computer programming and/or statistics to fulfill the requirements of their major(s) or other minor(s), or to fulfill their general education requirements, may not double-count those courses to reduce the total number of courses required for the minor in Digital Studies. In that case, they will take additional Digital Studies course(s) from the list under number 6 below.

Courses taken for the undergraduate minor in Digital Studies may not be double-counted with the student’s major(s), other minors, or general education requirements. Courses in the minor must be taken for quality grades, and more than half of the requirements for the minor must be met by registering for courses bearing University of Chicago course numbers.

1. One course in computer programming using the Python programming language: Either DIGS 20001, Introduction to Computer Programming with Python, which is offered annually in the Autumn Quarter, or CMSC 14100, Introduction to Computer Science I.

2. One course in quantitative data analysis: Either STAT 22000, Statistical Methods and Applications, which is offered every quarter, or DIGS 20002, Data Analysis I: Introduction to Statistics, which is offered annually in the Autumn Quarter. Note that STAT 20000, Elementary Statistics, does not fulfill this requirement, although STAT courses more advanced than STAT 22000 would do so.

3. One course in data management for the humanities: DIGS 20003, Data Management for the Humanities, which is offered annually in the Autumn Quarter.

4. One course in data publication for the humanities: DIGS 20005, Data Publication for the Humanities, which is offered annually in the Spring Quarter.

5. One elective course in the humanities or social sciences that deals with digital computing in some fashion, whether or not it entails actual coding. The elective course must be approved by the Associate Director of Curriculum and Instruction of the Forum for Digital Culture, or it may be chosen from a list of preapproved electives. The elective course may be one of the DIGS courses listed below under number 6.

6. One of the following Digital Studies courses:

    • DIGS 20004, Data Analysis II: Data Visualization and Machine Learning (Winter)
    • DIGS 20006, Artificial Intelligence and the Humanities (Spring)
    • DIGS 20007, Introduction to Digital Humanities (Winter)
    • DIGS 20021, Digital Archaeology (Spring)
    • DIGS 20031, Digital Texts I: Corpus Building and Corpus Statistics (Winter)
    • DIGS 20032, Digital Texts II: Advanced Topics in Textual Analysis (Spring)
    • DIGS 20041, Digital Media I: Game Design with Unity (Winter)
    • DIGS 20042, Digital Media II: Virtual Reality with Unity (Spring)

Please note the following prerequisites:

1. DIGS 20004, DIGS 20005, DIGS 20006, and DIGS 20007 each have as a prerequisite DIGS 20001 or an equivalent introduction to computer programming.

2. DIGS 20004 and DIGS 20006 also have as a prerequisite DIGS 20002 or an equivalent introduction to statistics.

3. DIGS 20006 also has as a prerequisite DIGS 20004 or an equivalent introduction to machine learning.

4. DIGS 20007 also has as a prerequisite DIGS 20003 or an equivalent introduction to digital knowledge representation and ontologies.

Scroll to Top