Data Science FAQ

Q:  Can I double major in Computer Science and Data Science?
A:  Yes.  However, keep in mind, this would require completing 2 senior projects/theses.  Starting in Fall 2020, these courses should be listed separately as CS/DS versions. 

Q:  Can I get a minor in Computer Science with a BS in Data Science?.
A:  Yes.  In fact, by completing the required courses in the BS in Data Science with sufficient GPA, the student will automatically earn a Minor in CS.

Q:  Can I apply for a BS/MS degree with the BS in Data Science, and the MS in Computer Science or Computing? 
A:  Yes.  Note that if one chooses the MS in Computer Science, then CS 6810 Computer Architecture would be required.  For that course, it is recommended to take CS 3810 Computer Organization during the BS part of the degree. 

Q:  Is there a Minor in Data Science? 
A:  There may be one in the future, but there are currently no concrete plans for which courses would constitute a minor. 

Q:  How do I apply for major status in Data Science? 
A:  We plan to open enrollment at the end of the Fall 2019 semester.  The process will mirror that for applying for major status in Computer Science. 

Q:  Can I use Math 1210, 1220 Calculus I, II in place of the BS in DS requirement for Math 1310, 1320 Engineering Calculus I, II?
A:  You can replace Math 1310, 1320 Engineering Calculus I, II with 3 courses:  Math 1210, 1220 Calculus I, II and Math 2210 Calculus III.  Without the Engineering Calc sequence, this additional Calc III course may be required for other requirements (e.g., Math 2270 Linear Algebra) or desired electives.

 

Q:  Can I take Electives (either Data Analysis Breadth  or  Data Domain ones) other than those listed in the degree map?
A:  Yes, with approval of the Director of the Data Science Program (currently Prof. Jeff Phillips).  Those are the pre-approved courses, but there are potentially many more that would qualify. 

The Data Analysis Breadth electives are meant to provide a broader picture of the array of  techniques in data science. 

The Data Domain electives are meant to expose students to a data rich domain (e.g., in Engineering, Science, Medicine, etc) where the other skills learned in the degree would be applicable.  These courses may be billed as “technique” or “technology” courses in their own disciplines, but from the perspective of a data science student, the working through of the in depth application of those techniques in that domain will be the desired aspect.  Indeed each domain often has its own specific data challenges, and being exposed and aware of these issues is an important outcome of taking such a course. 

In both cases, the courses do not need to be a specific sequence within a single data or technique domain.  They should suit the students interests and their overall educational and career plan. 

Q:  I cannot figure out how to register for the Data Wrangling course. 
A:  This course will be offered for the first time in Spring 2020.  The plan is that it will be taught every Spring thereafter.  It has a new course code DS.

Q:  Are the requirements for a Capstone Project (in CS 4000, CS 4500) or BS Thesis (CS 4940, CS 4970) the same as those for the Computer Science degree? 
A:  The project will need to have data science components, as approved by the Director of the Data Science Program.  In the near future this course requirement will be replaced with DS course codes (likely DS 4000, DS 4500, DS 4940, and DS 4970).  Initially these course will be co-located with the CS ones. 

Q:  Does the CS 4962 Ethics in Data Science course satisfy the Social/Behavior (BF) requirement?  If I already took that course, will I need to take another course to satisfy that requirement? 
A:  Currently it does not, but we plan to petition for it to satisfy that requirement after the Fall 2019 iteration is taught. 

Q:  My question was not asked/answered here.  How can I ask for clarification? 
A:  If a policy is not explicitly stated here, or answered in this FAQ, but there is a relevant one for Computer Science, as listed in the handbook, then the DS policy will default to that one.  This includes policies on Academic Misconduct, Non-Discrimination, and Sexual Misconduct — which conform to the University of Utah guidelines. 

Or you can use email DS-ugshelp@cs.utah.edu to contact the SoC undergraduate coordinators or the Director of the Data Science Program with additional questions.