Concentrations
Pure Mathematics
The Pure Math concentration lends itself to the advanced study of mathematics in graduate school. Students attending graduate school in math may become professors, researchers in national labs, or consultants. This concentration focuses more heavily on abstract mathematical thought and logic, and produces students who are not only proficient in reading and writing proofs, but are strong critical thinkers and problem solvers as well.
Applied Math
The Applied Math concentration focuses on applying mathematical ideas to specific problems in the sciences. Students graduating with an applied math concentration are prepared to go to school for engineering, to work for the government, to analyze data for scientifically oriented businesses, practice mathematical modeling to solve real world problems, or to train as financial analysts. Check out our Careers in Applied Math page to learn more.
Artificial Intelligence
The AI concentration explores the mathematical and algorithmic foundations of artificial intelligence (AI) techniques. Students will gain a solid background in AI both from a theoretical and applied perspective where they will build AI technologies across disciplines in a professional context. Core coursework will include mathematics for artificial intelligence, drawing from applied statistics, probability, calculus, and linear algebra and computer science, drawing from programming and algorithmic problem solving. Students will further broaden their understanding by applying their mathematical understanding to machine learning, deep learning, and artificial intelligence with the opportunity to complete an internship or applied research project in Data Science/AI, as supported by faculty mentorship and career services, to gain hands-on experience before graduation.
Accelerated BS-MS Artificial Intelligence and Data Science Degrees in 4.5 years
The AI concentration explores the mathematical and algorithmic foundations of artificial intelligence (AI) techniques. Students will gain a solid background in AI both from a theoretical and applied perspective where they will build AI technologies across disciplines in a professional context. Core coursework will include mathematics for artificial intelligence, drawing from applied statistics, probability, calculus, and linear algebra and computer science, drawing from programming and algorithmic problem solving. Students will further broaden their understanding by applying their mathematical understanding to machine learning, deep learning, and artificial intelligence with the opportunity to complete an internship or applied research project in Data Science/AI, as supported by faculty mentorship and career services, to gain hands‑on experience before graduation. Students will also take graduate courses in Data Science during their 4.5 years of study. Twelve credits of graduate study may be double counted for the 120 credits needed for the BS in Math undergraduate degree. The program will require students take 138 total credits (graduate and undergraduate) with 108 credits being exclusively from undergraduate courses and counted toward the undergraduate degree and 12 graduate credits being counted both as 12 undergraduate credits to complete the 120 credit undergraduate degree requirement and also as 12 graduate credits towards the 30 graduate credits required for the graduate degree.