Data Science
Bachelor of Science
Data Science
The B.S. in Data Science curriculum is designed to give students an interdisciplinary educational experience that provides a solid foundation in computer science, mathematics, and statistics. The curriculum prepares students to solve challenging data-driven problems across a variety of application areas. Students pursuing the B.S. in Data Science must declare an emphasis area in either Computer Science or Mathematics and Statistics. Courses within the emphasis areas provide more advanced discipline-specific content. Students can pursue interests aligned with specific data science applications (e.g., biology, business, economics) through free elective courses.
A minimum of 120 credit hours is required for a bachelor of science degree in Data Science. A minimum grade of “C” is required in each computer science, mathematics, and statistics course counted toward the B.S. in Data Science. These requirements for the B.S. degree are in addition to credit received for algebra, trigonometry, and basic ROTC.
| Freshman Year | |||
|---|---|---|---|
| First Semester | Credits | Second Semester | Credits |
| Basic ROTC (if elected)12 | 0 | Basic ROTC (if elected)12 | 0 |
| COMP SCI 15001 | 3 | Behavioral and Social Sciences Requirement6,9 | 3 |
| ECON 1100 or 1200 | 3 | COMP SCI 12001 | 3 |
| ENGLISH 1120 | 3 | COMP SCI 15701 | 3 |
| MATH 1101 or FR ENG 11001 | 1 | COMP SCI 15801 | 1 |
| MATH 1214 or 12111 | 4 | ENGLISH 1160 or SPM S 11854 | 3 |
| Natural Science Elective5 | 3 | MATH 12151 | 4 |
| 17 | 17 | ||
| Sophomore Year | |||
| First Semester | Credits | Second Semester | Credits |
| Basic ROTC (if elected)12 | 0 | Basic ROTC (if elected)12 | 0 |
| COMP SCI 15751 | 3 | COMP SCI 23001 | 3 |
| COMP SCI 15851 | 1 | COMP SCI 25001 | 3 |
| MATH 22221 | 4 | Humanities and Fine Arts Requirement7,9 | 3 |
| Natural Science Elective with Laboratory 5 | 4 | MATH 31081 | 3 |
| Statistics Requirement1,3 | 3 | STAT 5346 or COMP SCI 52041 | 3 |
| 15 | 15 | ||
| Junior Year | |||
| First Semester | Credits | Second Semester | Credits |
| COMP SCI 34021 | 3 | Electives2,11 | 6 |
| Electives - Emphasis Area1,2 | 6 | Electives - Emphasis Area1,2 | 6 |
| Humanities and Fine Arts Requirement7,9 | 3 | Humanities, Arts, and Social Sciences Requirement8,9 | 3 |
| STAT 53531 | 3 | ||
| 15 | 15 | ||
| Senior Year | |||
| First Semester | Credits | Second Semester | Credits |
| Electives - Emphasis Area1,2 | 6 | Electives - Data Science1,2,10 | 3 |
| Electives2,11 | 8 | Electives2,11 | 9 |
| 14 | 12 | ||
| Total Credits: 120 | |||
- 1
A minimum grade of “C” is required in each computer science, mathematics, and statistics course counted toward the B.S. in Data Science.
- 2
No course may be used to satisfy more than one degree requirement, except as otherwise noted.
- 3
The Statistics Requirement may be met by STAT 3113, STAT 3115, or STAT 3117.
- 4
May also be satisfied by ENGLISH 3560.
- 5
Natural sciences courses must be chosen from at least two specific disciplines: Biological Sciences (BIO SCI 1113 or higher), Chemistry (CHEM 1301 or higher), Geology (GEOLOGY 1110 or higher), or Physics (PHYSICS 1111 or higher). At least one credit hour of lab is required.
COMP SCI 5700 in the Computer Science emphasis area requires BIO SCI 1113 or BIO SCI 1213, which can be met as part of the Natural Sciences courses in the general education requirements.
- 6
The Behavioral and Social Sciences Requirement may be met by selecting one course from FRENCH 1101, FRENCH 1102, FRENCH 1180, GERMAN 1101, GERMAN 1102, GERMAN 1180, HISTORY 1100, HISTORY 1200, HISTORY 2110, PHILOS 1105, PHILOS 1115, POL SCI 1200, PSYCH 1101, RUSSIAN 1101, RUSSIAN 1102, RUSSIAN 1180, SPANISH 1101, SPANISH 1102, or SPANISH 1180.
- 7
The Humanities and Fine Arts Requirement may be met by selecting two courses from two different disciplines from HISTORY 1300, HISTORY 1310, HISTORY 2510, ART 1180, ART 3203, MUSIC 1150, THEATRE 1150, THEATRE 1190, ENGLISH 1211, ENGLISH 1212, ENGLISH 1221, ENGLISH 1222, ENGLISH 1231, ENGLISH 2230, ENGLISH 2232, ENGLISH 2240, ENGLISH 2250.
- 8
The Humanities, Arts, and Social Sciences Requirement may be met by selecting three additional credit hours from History, Art, Music, Theater, English and Technical Communication, Philosophy, Political Science, Psychology, Economics, Etymology, or Foreign Languages.
- 9
When selecting courses to fulfill the Behavioral and Social Science Requirement, the Humanities and Fine Arts Requirement, and the Humanities, Arts, and Social Sciences Requirement, you must select at least one course from HISTORY 1200, HISTORY 1300, HISTORY 1310, or POL SCI 1200 to satisfy the Williams Law requirement.
- 10
The Data Science elective course may be selected from the following:
COMP SCI 3200, COMP SCI 5206, COMP SCI 5300, COMP SCI 5400, COMP SCI 5401, COMP SCI 5402, COMP SCI 5411, COMP SCI 5420, COMP SCI 5421, COMP SCI 5700, ECON 5360, ECON 5380, ENG MGT 5414, MATH 3109, MATH 3304, MATH 5107, MATH 5601, MATH 5604, MATH 5670, MATH 5680, MATH 5737, MATH 5762, STAT 4210, STAT 5210, STAT 5270, STAT 5290, STAT 5364, STAT 5643, STAT 5644, STAT 5814, IS&T 5450, IS&T 5520.
No course may be used to satisfy more than one requirement in the B.S. in Data Science degree curriculum.
- 11
Sufficient free electives to earn a minimum of 120 credit hours.
- 12
Basic ROTC may be elected in the freshman and sophomore years, but is not creditable toward a degree. Up to six credit hours of advanced ROTC may be credited as free electives towards a degree.
Emphasis Areas
Computer Science Emphasis Area
Required courses:
| COMP SCI 5206 | Probability and Its Applications in Computing | 3 |
| COMP SCI 5400 | Introduction To Artificial Intelligence | 3 |
| COMP SCI 5420 | Introduction to Machine Learning | 3 |
| or COMP SCI 5402 | Introduction to Data Mining | |
| COMP SCI 5421 | Reinforcement Learning | 3 |
| COMP SCI 5480 | Deep Learning | 3 |
| COMP SCI 5700 | Bioinformatics | 3 |
Mathematics and Statistics Emphasis Area
Required courses:
| STAT 5643 | Probability And Statistics | 3 |
| STAT 5644 | Mathematical Statistics | 3 |
| MATH 5670 | Scientific Programming with Python | 3 |
| Select three of the following: | ||
| MATH 3109 | Foundations Of Mathematics | 3 |
| MATH 5680 | Mathematics of Machine Learning | 3 |
| STAT 4210 | Introduction to Statistical Data Science | 3 |
| STAT 5364 | Causal Data Science | 3 |