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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:

 

Fall First Year - 4 units

Spring First Year - 4 units

F1: First Year Seminar

F2: MATH 170

F3: Foreign Language

M4: ECON 152

F4: CSCI-120

MATH 171

ACCT 157

F3: Foreign Language II

Fall Second Year - 4 units

Spring Second Year - 5 units

CSCI 210: Data Wrangling

MATH 232

ECON 225

M: 1,2,3,5,6 (choice)

CSCI 265

MATH 338

ECON 226

MGMT 251 (or other elective)

M: 1,2,3,5,6 (choice)

Fall Third Year - 4.5 units

Spring Third Year - 4 units

MATH 231

CSCI 243.2 (0.5 units)

ECON 256 (D.S. elective)

M: 1,2,3,5,6 (choice)

Free elective

MGMT 311 (D.S. elective)

ECON/MGMT 231

U: 1,2 (choice)

M: 1,2,3,5,6 (choice)

Fall Fourth Year - 3.25 units UG, 6 credits graduate

Spring Fourth Year - 3.25 units UG, 6 credits graduate

Free Elective

Free Elective

Free Elective

 

Graduate: (0.75 units go towards UG)

MGMT 513: Leading People in Organizations (0.75 units, 3 credits)

MGMT 511: Dev. Leadership Competencies

 ( 3 credits)

CSCI 334

Free Elective

Free Elective

 

Graduate: (0.75 units go towards UG)

MGMT 553: Big Data Management (0.75 units, 3 credits)

MGMT 557: Big Data Analytics, 3 credits)

Summer I Fourth Year - Graduate (3 crdt)

Summer II Fourth Year - Graduate (3 crdt)

MGMT 577: Project Management & Planning

MGMT 602: Multivariate Analysis

Fall Fifth Year - Graduate (9 credits)

Spring Fifth Year - Graduate (9 credits)

MGMT 555: Business Research Methods

MGMT 605: Generalized Linear Models

MGMT 608: Advanced Modeling Techniques

MGMT  618 Data Visualizations

MGMT 556: Decision Analysis

MGMT 671: Capstone Project