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Department of Computer Science

Bachelor of Science in Data Science

Co-Directors: Associate Professor Alva Couch (Computer Science) and Associate Professor Shuchin Aeron (Electrical and Computer Engineering)

Data Science refers to the principles and practices in data analysis that support data-centric real-world problem solving. The Bachelor of Science in Data Science (BSDS), jointly administered by the departments of Computer Science and Electrical and Computer Engineering, is offered to students in the School of Engineering who desire to concentrate on applying computing to scientific and engineering analysis and problem solving. The BSDS is designed both as a stand-alone major and a double major option for those students in the School of Engineering who wish to add data science to an existing engineering major. The BSDS degree is only available to students in the School of Engineering.  Double majoring in the B.S.D.S. and Bachelor of Science in Computer Science (BSCS) programs is not practical and will not be permitted due to overlap between the major concentrations. 
The mission of the BSDS is to prepare students for Data Science careers in engineering, science, medicine, and other disciplines. The objectives of the BSDS program include that graduates should have, after five years: 

  1. Succeeded and advanced in professional careers in or related to data science, analysis, and interpretation, and/or
  2. Been admitted to and advanced in graduate study in data science and related fields. 

The outcomes of the Bachelor of Science in Data Science include the following:

  1. Graduates will demonstrate facility in a variety of data analysis techniques, including machine learning, optimization, statistical decision-making, information theory, and data visualization. 
  2. Graduates will be qualified to engage in interdisciplinary projects with data analytics components, including facility in communicating with engineers, scientists, and computing professionals. 
  3. Graduates will have been exposed to the ethical and scientific obligations of the data analyst. 

The BSDS is not accredited by the Computing Accreditation Commission or Engineering Accreditation Commission of ABET. For an ABET-accredited degree, see the Bachelor of Science in Computer Science (BSCS), Bachelor of Science in Computer Engineering (BSCpE), or Bachelor of Science in Electrical Engineering (BSEE). 

Requirements

The Bachelor of Science in Data Science (BSDS) requires a minimum of 120 semester-hours of study, including introductory, foundation, HASS, breadth, and concentration courses. Introductory courses (10 courses) include an Engineering 1 course; Engineering Science 2; Mathematics 32, 34 or 39, 42 or 44; Mathematics 65 and Mathematics 70 or 72; Physics 11; Chemistry 1 or 16; one of Physics 12, Chemistry 2, or Biology 13; and a natural science elective. For natural science courses accepted towards the Engineering degrees, refer to the online course catalog for courses with attribute "SOE-Natural Science."

The Humanities, Social Sciences, and Arts (HASS) requirement (24 semester hour units) includes English 1 or 3 and additional courses in Humanities, Arts, or Social Sciences. Of these courses, one course must cover ethics and social context (Engineering Management 54 or Philosophy 24), one course worth at least 3 semester hour units must be in Humanities, and one course worth at least 3 semester hour units must be in Social Science. Allowable courses in Humanities, Arts, and Social Sciences are listed in the online course catalog with attribute "Engineering Requirements" and possible values "SOE- HASS-Humanities," "SOE-HASS-Arts," and “SOE-HASS-Social Sciences,” respectively; courses labeled with a value of "SOE-HASS" are also acceptable. Philosophy 24 does not satisfy the requirement for three credit hours in Humanities unless Engineering Management 54 is also taken. 

The disciplinary breadth requirement includes nine semester hour units of courses in some application discipline related to Data Science.  Ideally, all of the 9 semester hour units should be in the same discipline, though it is permissible for 3 semester hour units of the 9 to come from a second discipline. Appropriate choices include: 

  1. Any three courses in one natural science; courses must be in the same department with SIS attribute "Engineering Requirements" and value "SOE-Natural Sciences."
  2. Any three courses in one social science; courses must be the same department with attribute "Engineering Requirements" and value "SOE-HASS-Social Sciences."
  3. Any three courses in the department of Civil and Environmental Engineering.
  4. Any three courses in the Classics department.

See the "Guide to the Data Science Major in Engineering" for more specific course recommendations. Students may also petition the Program Directors to count a customized multi-disciplinary experience toward this requirement. 

The Engineering requirement (two courses) includes Engineering 1 and Engineering Science 2.

The Data Science major requirement (12 courses) includes Computer Science 11, 15, 40, 135, and 160, Mathematics 165 or Electrical Engineering 24 or 104, Mathematics 166, Mathematics 126 or Computer Science 136, and four Data Science electives, three of which must be numbered above 100. Those three must include: (A) one course in data infrastructure (including Computer Science 51, 112, 115, 116, 117, 118, 119, 120, and 151); (B) one course in data analytics and/or interfaces (including Computer Science 52, 136, 137, 138, 141, 142, 152, 171, 175, 177, and 178; Mechanical Engineering 150; and Civil and Environmental Engineering 187); and (C) one course in computational and theoretical aspects of data science (including Computer Science 131 and 160; Data Science 53 or 153 (or Computer Science 53 or 153); Mathematics 123, 125, and 126; and Electrical Engineering 109, 127, 130, 133, and 140); plus one additional course chosen from (A)-(C) or from Mathematics 133, 153, 155, and 156. At most three semester hour units of Independent Study or Research (Computer Science 93, 94, 191, 193, or 194; Electrical Engineering 93, 94, 95, 96, 191, or 192) and at most four semester hour units of thesis (Computer Science 197 or Electrical Engineering 197) may be counted as Data Science electives. A capstone experience including the two courses Data Science 97 and Data Science 98 (Senior Capstone Project in Data Science I and II) is required. For a research experience, students should consider partly fulfilling concentration elective requirements via a senior thesis, coordinated with the capstone experience and breadth elective choices.

While only one of Mathematics 126 or Computer Science 136 is required among the concentration classes, students are encouraged to take both classes using a data science elective slot. 

The following sample program is one way of satisfying the above requirements.

First Year 
FALL TERM 

  • Engineering 1
  • Mathematics 32 (or 39)
  • Physics 11, Chemistry 1 or 16, or Biology 13
  • English 1 

SPRING TERM 

  • Mathematics 34
  • Computer Science 11 Introduction to Computer Science 
  • Physics 11, Chemistry 1 or 16, or Biology 13
  • Natural Science Elective

Sophomore Year 
FALL TERM 

  • Computer Science 15 Data Structures 
  • Mathematics 42 or 44 Multivariate Calculus
  • Mathematics 65 Foundations of Higher Mathematics 
  • Biology, Chemistry, or Physics Depth Elective.
  • Humanities, social sciences, or arts elective

SPRING TERM 

  • Mathematics 70 or 72
  • Engineering Management 54 Engineering Leadership 
  • Computer Science 40 Computer Architecture  
  • Data science elective
  • Humanities, social sciences, or arts elective

Junior Year 
FALL TERM 

  • Computer Science 135 Machine Learning
  • Probability (Electrical Engineering 24 or Mathematics 165)  
  • Data science elective
  • Disciplinary breadth elective
  • Humanities, social sciences, or arts elective

SPRING TERM 

  • Mathematics 166 Statistics 
  • Computer Science 160 Algorithms
  • Data science elective
  • Disciplinary breadth elective
  • Humanities, social sciences, or arts electives

Senior Year 
FALL TERM 

  • Data Science 97 Senior Capstone Project in Data Science I 
  • Data science elective
  • Data science elective
  • Disciplinary breadth elective
  • Humanities, social sciences, or arts elective

SPRING TERM 

  • Data Science 98 Senior Capstone Project in Data Science II 
  • Mathematics 126 Numerical Linear Algebra
  • Data science elective
  • Humanities, social sciences, or arts elective

ABET accreditation

The BSDS is not accredited by the Computing Accreditation Commission or Engineering Accreditation Commission of ABET. For an ABET-accredited degree, see the Bachelor of Science in Computer Science (BSCS), Bachelor of Science in Computer Engineering (BSCpE), or Bachelor of Science in Electrical Engineering (BSEE).

Forms

All forms for CS undergraduate students.

Guide to Data Science major

Additional information

Forms for undergraduates