Proposed Mathematics Undergraduate Major (Concentration) in Data Analytics

Prerequisites:

ITCS 1212/1212L (also required for MATH BA/BS)

ITCS 1213/1213L

ITCS 2214 (Data Science)

MATH 1241/1242/2241 (Calculus I – III)

MATH 2164 (Linear Algebra)

Core courses:

ITCS 3162 (Intro Data Mining)

MATH 3122/3123 (Probability & Statistics I & II)

STAT 3110 (Linear Regression) or STAT 3126 (Applied Statistical Methods)

STAT 4116 (Statistical Computing) or STAT 4123/4124 (Applied Statistics I & II)

Suggested Courses:

Shared with Computer Science BS – Data Science Concentration:

ITCS 3160 (Database Implementation and Design)

(9 credits, at least one from group A and group B)

Group A:

  • ITCS 3156 Machine learning ITCS 3216 Intro to Cognitive Science
  • Nonlinear Programming
  • ITCS 3190 Cloud computing

Group B:

  • ITCS 4122 visual analytics
  • ITCS 3134 image processing
  • INFO 3236 Business analytics
  • ITIS 4510 Web mining

Shared with BCOB BS – Business Analytics Concentration:

Econ 3112 (Econometrics)

INFO 3236 (Business Analytics)

Electives:

Anyother MATH/STAT or ITCS/ITIS or BCOB 3xxx/4xxx courses (also see HTAS Minor – Data Science Ethics concentration description below)

Future Department-Related Projects

  • Joint Mathematics/Statistics/Political Science major: It is noted that more and more of the graduate work in Public Policy is quantitative and growing numbers of graduate students in this area are coming from quantitative backgrounds; such a major would with a comprehensive and integrated approach reflect and support this trend.
  • Course Development Collaboration with Computer Science: The CS department has identified a need within their proposed Data Science concentration for a course or courses dealing with the language R and scripting (e.g. Python) includingrelevant topics in the design of experiments and instructional data. They have proposed developing this coursework jointly with the MATH/Stat department given the overlapping nature of the subjects involved. Given the overlap such coursework should also have a useful place in our department’s proposed DA concentration.

Notes:

1)The proposed data analytics concentration above complements data science and business analytics concentrations proposed by the Computer Science Department and the College of Business, with each of the three concentrations reflecting their respective unit emphases. There is a consensus among the coordinators and chairs of the participating departments to have all three concentrations listed together on one website (while maintaining links on their own websites) and for each unit to extract a minor from their concentration to also feature on the central site. The purpose here is to facilitate more options and flexibility for students to tailor their interdisciplinary exposure according to their background and tastes.

2)In relation to the potential collaboration on a joint major with the Department of Political Science, the trend toward more quantitative emphasis on graduate work in public policy is reflective of relevant potential employer interest particularly among nonprofit organizations involved in social engagement.