Dec 03, 2024  
2020-2021 UMass Dartmouth Undergraduate Catalog 
    
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2020-2021 UMass Dartmouth Undergraduate Catalog [Archived Catalog]

Data Science

BS Degree

The purpose of the program is to prepare students for technology-based careers in fields that require computer programming, data analysis, visualization, and a flexible, broad understanding of informatics. It is intended to appeal to students who want to learn technological and analysis tools used by today’s science, engineering, business, and government organizations.

The program is designed to provide students with first-rate skills and knowledge in computer science, mathematics, statistics, and a relevant substantive field of study with databases of exceedingly large size, so that students can learn statistical modeling and computer-based operations to index, store, extract, analyze, display, and interpret from those computerized databases. The growth in size of databases and the need to be able to “analyze and mine” them is one of the chief challenges for knowledge development and discovery in the 21st century.

Data Science is an interdisciplinary area that draws upon the traditionally distinct areas of computer science, applied mathematics and statistics, and applications from natural and social sciences, engineering, and business. Graduates from the BS program in Data Science will acquire the skills necessary to manage and analyze massive data sets. A Body of Knowledge for the subject is presented below:

Statistics

  • Exploratory data analysis
  • Stratified sampling
  • Regression, linear models
  • Goodness of fit of statistical models
  • Analysis of variance
  •  Design of experiments
  • Digital signal processing

Machine Learning (quantitative analysis)

General Programming Ability

  • Python and pandas
  • R
  • MATLAB, Maple, Mathematica
  • MapReduce/Hadoop
  • High Performance Computing (e.g. via MATLAB)
  • Databases: MySQL

Data Communication

  • Data visualization
  • Web programming: HTML5, CSS, PHP, JavaScript

Calculation of the GPA in the Data Science Major

Students must have a minimum 2.000 cumulative grade point average (GPA) for all courses taken at the University in order to graduate. Students must also have a minimum 2.000 cumulative GPA in the major. For purposes of this computation:

  1. All required courses with a CIS, DSC, and MTH prefix count in calculating the GPA for the Data Science major.
  2. If a course is repeated, only the most recent course grade (whether higher or lower) shall be used to calculate the major cumulative GPA. Repeated courses are subject to the University’s course repeat policy.

Requirements

Students must maintain a minimum grade of ‘C’ in each CIS course and a minimum grade of ‘C-’ in each MTH course leading to the DSC degree.

First Year

First Semester - 17 credits

  • University Studies Requirement Credits: 3 (see Footnote 1 below)

Second Semester: 14 credits

  • University Studies Requirement Credits: 3 (see Footnote 1 below)

Second Year

First Semester - 16 credits

  • Free Elective Credits: 3
  • Laboratory Science Requirement Credits: 4 (see Footnote 2 below)

Second Semester - 14 credits

  • Laboratory Science Requirement Credits: 4 (see Footnote 2 below)

Third Year

First Semester - 15 credits

  • University Studies Requirement Credits: 3 (see Footnote 1 below)
  • Science/Quantitative Elective Credits: 3 (see Footnote 3 below)

Spring Semester - 15 credits

  • University Studies Requirement Credits: 6 (see Footnote 1 below)
  • Free Elective Credits: 3

Fourth Year

First Semester - 15 credits

  • Free Elective Credits: 6 (see Footnote 4 below)
  • Technical Elective Credits: 3 (see below)

Second Semester - 14 credits

  • Free Elective Credits: 3
  • Technical Elective Credits: 6 (see below)

Technical Electives

Must be taken from approved list of courses. Students should speak with their advisor before selecting technical electives. Note: CIS 430 or CIS 452 can count as a Technical Elective only if the course is not used to meet the Core Requirements above.

Total Credits: 120

Footnotes

[1] See University Studies requirements, Clusters 3 and 4. 

[2] Complete one of the following sequences in Laboratory Science:

  • BIO 121/131 and BIO 122/132
  • CHM 151/161 and CHM 152/162
  • PHY 113 and PHY 114

[3] Science electives are any course in BIO, CHM, MAR, MLS or PHY. Students should choose a course that has also been approved to meet the University Studies Cluster 2A requirement if Chemistry has been completed for the laboratory science requirement.

[4] Up to three credits of EGR 490, Engineering Internship, can be counted as a Free Elective. EGR 490 must be approved by the Faculty Sponsor, Program Chair, and Associate Dean prior to the start of the internship.

University Studies Requirements for Data Science

Degree candidates for the BS degree in Data Science must satisfy the University Studies requirements as described in the Academic Policies section of this catalogue.

  • University Studies requirements in Clusters 1, 2B, and 5 are automatically satisfied by the courses shown as required for this major.
  • The University Studies requirements in Clusters 2A, 3, and 4 may be fulfilled by selecting courses from the approved lists in each cluster, using the University Studies electives shown in the course requirement tables for each major.

University Studies Departmental Requirements

Students majoring in Data Science will meet their departmentally determined University Studies requirements as follows:

Cluster 1

Cluster 2

Cluster 5

Math Placement

Students not starting in Calculus (MTH 151) will be placed in Pre-Calculus (MTH 150) or Pre-Calculus Enhanced (MTH 150E) in the first semester. This delays the start of Calculus to the spring semester, which may then extend the program beyond four years.