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Data Science Major

Data Science is inherently interdisciplinary, intersecting the fields of statistics, computer science, and mathematics. The data science major provides students with a mathematical foundation in calculus and probability, the technical and problem-solving skills for curating and wrangling data along with a foundation in building and assessing statistical models to analyze data and effectively communicate their results. The major also emphasizes the importance of effectively working in a team and being responsible consumers of data.

The Data Science major consists of 7.5 units of required courses, 3 units of electives courses, and 2 units of co-requisite courses.

Required Courses:

• CSCI 120 Introduction to Computer Science
• CSCI 210 Data Wrangling
• CSCI 265 Database Systems
• MATH 231 Mathematical Statistics 1
• MATH 232 Applied Statistics
• MATH 338 Applied Statistical Modeling
• One of :
  • CSCI 334 Computer Science Capstone
  • 300-level Internship in Mathematics or Computer Science
  • CSCI 400/401 Honors
  • CSCI 243.2 Preparing for a Computing Career (junior standing)

Electives:

Students must complete three units of additional elective courses numbered 210-299 or 310-399, with at least two courses numbered 310-399 from:

• Any course in MATH or CSCI
• ECON 256 Applied Econometrics (prereqs: a course in statistics and ECON 152, which is recommended as the M4 for students in data science)
• ENVR 210 Intro to Geographic Information Systems (sophomore standing)
• HLTP 230 Epidemiology
• MKTG 311 Marketing Research (prereq: MKTG 251; plus MATH 107, MATH 232 or ECON 156)
• BIOL 363 Genomics (prereqs: BIOL 111 and BIOL 210 and permission of the instructor)
• BIOL 220 Biostatistics (prereqs: BIOL 111 or ENVR 112 and MATH 166 or MATH 170 or MATH 107 or ECON 156)
• PSYC 211 Experimental Methods and Data Analysis I (prereq: PSYC 120)
• SOC 246 or 346 Basic Research Methods/Advanced Research in Sociology (prereq: SOC 115)
• Or a course approved by the department

Co-requisites:

• MATH 170 Calculus 1 (or MATH 106 Analytic Geometry and Calculus I with Review, Part 1 and MATH 166 Analytic Geometry and Calculus I with Review, Part 2)
• MATH 171 Calculus

This major can lead into the Masters of Data Analytics (MSDA) program. If the student takes the following courses as electives they will meet the requirements for admission to the program:

• ECON 152: Principles of Economics - recommended M4 course for data science students
• ECON 225 Microeconomics (prereq: MATH 170 or MATH 106/166)
• ECON 226 Macroeconomics (prereq: ECON 152 and ECON 156*)
• ECON/MGMT 231 Managerial Finance (prereq: ECON 152, ECON 156*, ACCT 157)

*MATH 232 can be used instead of ECON 156, and it is a requirement for the data science major.

Students can complete a 4+1 program where the student completes the last few Data Science undergraduate major requirements during their fourth year while starting to take graduate courses for the MSDA program and completes that program during the fifth year. The following is an example schedule that would work: