Nov 21, 2024

2024-2025 Undergraduate Catalog

Data Science, B.S.

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More Information about Department of Mathematics and Computer Science :

A minimum of 120 credit hours is required for a Bachelor of Science in Data Science.

The data science major weaves together traditional curriculum in mathematics and computer science along with curriculum related to current data science techniques to prepare graduates for employment as data science practitioners. Additionally, the major relies on the Core curriculum to develop key communication and ethical thinking skills that are critical to success in data science. Technical skills are focused not only data and programming, but mathematical thinking as well. The goal is to develop individuals that are capable of using these foundational skills to independently expand their expertise into constantly evolving new algorithmic and programming approaches as the field continually evolves. Application areas within the curriculum framework enable students to explore a variety of cross-disciplinary application domains in order to prepare for data science careers within specific domains. Current application areas include Analytics for Business, Computational Science, Data Engineering, Operations Research, and Cyber Analytics.

Major Requirements

49 credits total, includes the 15 credit application area

CMSCI 120 - Introduction to Computer Science I Credits: (3)
CMSCI 125 - Introduction to Computer Science II Credits: (3)
CMSCI 254 - Data Structures and Algorithms Credits: (3)
DATA 200 - Introduction to Data Science Credits: (3)
3 credits of DATA 201 ST: Data Science are required
- DATA 201 ST: Special Topics in Data Science Credits: (1)
- DATA 201 ST: Special Topics in Data Science Credits: (1)
- DATA 201 ST: Special Topics in Data Science Credits: (1)
DATA 210 - Exploratory Data Analysis Credits: (3)
DATA 220 - Machine Learning Models Credits: (3)
DATA 475 - Data Science Capstone Credits: (3)
Choose One Data Skills Elective:
- CMSCI 359 Database Management Systems Credits:(3)
- DATA 320 Distributed Data Systems Credits: (3)
- DATA 330 Data Wrangling Credits: (3)
- DATA 340 Advanced Data Visualization Credits:(3)
MATH 247 - Calculus I Credits: (4)
MATH 364 - Linear Algebra Credits: (3)
Choose One Application Area and complete 15 credits within that area, three of which must be at the 300-level or above:

Computational Science Application Area

15 credits required

CMSCI 349 - Software Engineering Credits: (3)
CMSCI 359 - Database Management Systems Credits: (3) *
CMSCI 449 - Intro to Artificial Intelligence Credits: (3)
DATA 330 - Data Wrangling Credits: (3)
DATA 340 - Advanced Data Visualization Credits: (3)
DATA 350 - Natural Language Processing Credits: (3)
DATA 410 - Advanced Machine Learning Credits: (3)
DATA 420 - High Performance Computing Credits: (3)
DATA 430 - Network Science Credits: (3)
DATA 492 - Practicum Credits: (1-3)
MATH 387 - Probability Credits: (3)
MATH 388 - Operations Research Credits: (3)
MATH 389 - Numerical Methods Credits: (3)
MATH 228 - Discrete Mathematics Credits: (3)
MATH 489 - Modeling and Simulation Credits: (3) OR CMSCI 489 Modeling and Simulation Credits:(3)
NOTE

* CMSCI 359, DATA 320, DATA 330 and DATA 340 - These courses cannot be double-counted as the Data Skills Elective for the major and credit towards and Application Area.

Cyber Analytics Application Area

15 credits required

CMSCI 349 - Software Engineering Credits: (3)
CMSCI 355 - Network Systems and Design Credits: (3)
CMSCI 358 - Computer Security I Credits: (3)
CMSCI 359 - Database Management Systems Credits: (3) *
CYBER 301 - Secure Systems Design & Risk Mgmt. Credits: (3)
CYBER 357 - Network Security Credits: (3)
DATA 320 - Distributed Data Systems Credits: (3) *
MATH 228 - Discrete Mathematics Credits: (3)

Data Engineering Application Area

15 credits required

CMSCI 349 - Software Engineering Credits: (3)
CMSCI 359 - Database Management Systems Credits: (3) *
CMSCI 460 - Database Implementation Credits: (3)
DATA 320 - Distributed Data Systems Credits: (3) *
DATA 330 - Data Wrangling Credits: (3)
DATA 340 - Advanced Data Visualization Credits: (3)
DATA 350 - Natural Language Processing Credits: (3)
DATA 430 - Network Science Credits: (3)

Operations Research Application Area

15 credits required

MATH 228 - Discrete Mathematics Credits: (3)
MATH 332 - Graph Theory Credits: (3)
MATH 387 - Probability Credits: (3)
MATH 388 - Operations Research Credits: (3)
MATH 389 - Numerical Methods Credits: (3)
MATH 390 - Mathematical Statistics Credits: (3)
MATH 464 - Advanced Linear Algebra Credits: (3)
MATH 489 - Modeling and Simulation Credits: (3) OR CMSCI 489 Modeling and Simulation (3)

Analytics for Business Application Area

15 credits required

BUS 250 - Intro to Business & Decision Making Credits: (3)
BUS 313 - Principles of Marketing Credits: (3)
BUS 344 - Operations and Supply Chain Mgmt. Credits: (3)
BUS 350 - Marketing Research Credits: (3)
BUS 375 - Project Management Credits: (3)
BUS 430 - Advanced Supply Chain Management Credits: (3)
ECON 211 - Intermediate Macroeconomic Theory Credits: (3)
ECON 402 - Applied Economic Analysis Credits: (3)
ECON 403 - Econometrics Credits: (3)
* This course cannot be double-counted as the Data Skills Elective for the major and credit towards an Application Area.

Natural Science Application Area

15 Credits Required

BIOL 259 - Intro to Bioinformatics Credits: (0-4)
Complete three additional courses from the below:
BIOL 221 - Genetics Credits: (4)
BIOL 400 - Toxicology Credits: (4)
BIOL 420 - Molecular and Cellular Biology Credits: (4)
BIOL 435 - Cancer Biology Credits: (4)
BIOCH 405 - Biochemistry I Credits: (4)
CHEM 303 - Physical Chemistry I Credits: (5)

Note

To earn a Bachelor of Science in Data Science, students must complete a minimum of 120 credit hours. Students must also earn a major GPA of 2.0, and a cumulative GPA of 2.0.

Core Requirements (46 to 49 credits)

The First Year Symposium (3 credits)

Complete the First Year Symposium

FSYM 101 - The First Year Symposium Credits: (3)
Students who cannot complete First Year Symposium must pass one of the following composition courses:
COMM 200 - Foundations of Writing Credits: (3)
COMM 125 - Essentials of Speaking and Writing Credits: (3)
GENED 104 - Work and Education Credits: (3)

World Language Requirement (3-6 Credits)

Complete either 6 credits at the 101 and 102 level or 3 credits at the 200 level or above

Introductory Language (For students beginning at the 101 level)
- XXXX 101 (3)
- XXXX 102 (3)
Advanced Language (For students who begin at the 201 level or above)
- XXXX 201/301 (or higher).

Foundations of Social Science (3 Credits)

Choose 3 credits from among the following:

CJUST 110 - Introduction to Criminal Justice Credits: (3)
ECON 101 - Foundations of Economics: Macroecon Credits: (3)
ECON 102 - Foundations of Economics: Microecon Credits: (3)
EDUC 100 - Foundations of American Education Credits: (4)
PSCI 100 - Foundations of American Government Credits: (3)
PSYCH 100 - Foundations of Psychology Credits: (3)
SOC 100 - Foundations of Sociology Credits: (3)

Modernity in Literature or the Arts (3 Credits)

Choose from among one of the following:

ARMO 300 - Modernity in Visual Art Credits: (3)
ENMO 300 - Modernity in Literature Credits: (3)
MUMO 300 - Modernity in Music Credits: (3)
THMO 300 - Modernity in Theatre Credits: (3)

Laboratory Science (3-4 Credits)

Choose one laboratory science course:

BIOL 110 - Introduction to Biology I Credits: (4)
BIOL 111 - Introduction to Biology II Credits: (4)
BIOL 298 - Anatomy and Physiology I Credits: (4)
CHEM 101 - General Chemistry I Credits: (4)
PHYS 101 - College Physics I Credits: (4)
PHYS 201 - General Physics I Credits: (4)
GNSCI XXX: General Science Course: Credits (3)

Global Encounters (3 Credits)

Choose one Global Encounters course:

XXGE Global Encounters
- Global Encounters courses are offered in many departments, including Business, Communication, English, Education, Foreign Language, History, Philosophy, Political Science, Psychology, Sociology and Theology.

Ethics and the Human Good (3 Credits)

Complete one of the following:

PHIL 300 - Ethics and the Human Good Credits: (3)
THEOL 300 - Ethics and the Human Good Credits: (3)

Ethical Leaders (0 Credits)

The Ethical Leadership Experiential Learning Core Requirement invites students to integrate their own personal call to leadership with a mature reflection on one or more of the core virtues of Justice, Courage, Integrity, and Humility. Students will accomplish this by engaging in and reflecting upon the practice of virtue ethics within the context of one or more experiential learning activities.

Sample Four Year Sequence

Freshman Year

Fall Semester

FSYM 101 The First Year Symposium (3)

World Languages I (3)

MATH 211 Mathematical Thinking (3)

CMSCI 120 Introduction to Computer Science I (3)

DATA 200 Introduction to Data Science (3)

15 credits

Spring Semester

WCIV 102 Origins of the West (3)

World Languages II (3)

PHIL 103 Foundations of Philosophy (3)

CMSCI 125 Introduction to Computer Science II (3)

DATA 210 Exploratory Data Analysis (3)

15 credits

Sophomore Year

Fall Semester

WCIV 201 Atlantic Encounters: 1450-1850 (3)

PHIL 203 Philosophy in the Modern Age (3)

CMSCI 254 Data Structures and Algorithms (3)

DATA 220 Machine Learning Models (3)

MATH 247 Calculus I (4)

16 credits

Spring Semester

THEOL 220 Foundations of Theology (3)

AMER 202 America in the World (3)

Foundations in Social Science (3)

MATH 364 Linear Algebra (3) *

DATA XXX Data Skills Elective (3)

DATA 201 ST: Special Topics in Data Science (1)

16 credits

Junior Year

Fall Semester

XXMO 300 Modernity in Lit./Art/Music/Theatre (3)

THEOL 320 Made In God’s Image (3)

XXX XXX Application Area Elective (3)

Elective (3)

DATA 201 ST: Special Topics in Data Science (1)

16 credits

Spring Semester

THEOL/PHIL 300 Ethics and the Human Good (3)

XXGE 3XX Global Encounters (3)

XXX XXX Application Area Elective 300-level or above (3)

Elective (3)

GNSCI 1XX Lab Science (4)

16 credits

Senior Year

Fall Semester

XXX XXX Application Area Elective 300-level or above (3)

DATA 201 ST: Special Topics in Data Science (1)

Elective (3)

13 credits

Spring Semester

DATA 475 Data Science Capstone (3)

Elective (3)

15 credits

* It is recommended that MATH 364 Linear Algebra (3) be taken as early as possible after the freshman year.

Additional Notes:

Several courses can be double-counted so that a double major with mathematics or with computer science can be completed in 65 credits and a double major with cybersecurity can be completed in 67 credits.