Bachelor of Science in Data Science (Mathematics)
About This Program
The Bachelor of Science in Data Science Mathematics concentration enhances theoretical and computational skills by blending advanced mathematics with algorithm design and statistical modeling. Students gain a deeper understanding of the mathematical principles that underlie modern data analysis, artificial intelligence, and other computational applications. Beyond the UTA Core Curriculum requirements, the degree requires a sequence of courses in Mathematics, Data Science, and Mathematics. In addition, students must complete a year-long Capstone project in collaboration with a supervisor within the College of Science or an Industry Partner.
Competencies
- Upon completion, students will demonstrate knowledge of fundamentals of mathematics and statistics, in applications to data science.
- Upon completion, students will demonstrate knowledge of computer programming through receiving a certificate, and therefore passing, a programming course.
- Upon completion, students will demonstrate the ability to effectively work in teams to complete data science projects
Curriculum
| Foundations | ||
| General Core Requirements | 42 | |
| Students must complete specific courses in certain core areas. | ||
| For Communication select: | ||
| RHETORIC AND COMPOSITION I | ||
An additional communication area course. | ||
| For Life & Physical Science select one of the following sequences: | ||
| BIOLOGY I FOR SCIENCE MAJORS: CELL AND MOLECULAR BIOLOGY and BIOLOGY II FOR SCIENCE MAJORS: ECOLOGY AND EVOLUTION | ||
| GENERAL CHEMISTRY I and GENERAL CHEMISTRY II | ||
| GENERAL TECHNICAL PHYSICS I and GENERAL TECHNICAL PHYSICS II | ||
| EARTH SYSTEMS and EARTH HISTORY | ||
| For Mathematics select: | ||
| CALCULUS I | ||
| Data Science Foundations | ||
| UNIV 1131 | STUDENT SUCCESS | 1 |
| or UNIV-SC 1101 | CAREER PREPARATION AND STUDENT SUCCESS | |
| Additional hours required in core. | 1 | |
| MATH 2425 | CALCULUS II | 4 |
| Data Science Specialization | ||
| DATA 3401 | PYTHON FOR DATA SCIENCE 1 | 4 |
| DATA 3402 | PYTHON FOR DATA SCIENCE 2 | 4 |
| DATA 3421 | DATA MINING, MANAGEMENT, AND CURATION | 4 |
| DATA 3441 | STATISTICAL METHODS FOR DATA SCIENCE 1 | 4 |
| DATA 3442 | STATISTICAL METHODS FOR DATA SCIENCE 2 | 4 |
| DATA 3461 | MACHINE LEARNING | 4 |
| DATA 4380 | DATA PROBLEMS | 3 |
| DATA 4381 | DATA CAPSTONE PROJECT 1 | 3 |
| DATA 4382 | DATA CAPSTONE PROJECT 2 | 3 |
| Mathematics Specialization | ||
| MATH 2326 | CALCULUS III | 3 |
| MATH 3300 | INTRODUCTION TO PROOFS | 3 |
| MATH 3302 | MULTIVARIATE STATISTICAL METHODS | 3 |
| MATH 3313 | INTRODUCTION TO PROBABILITY | 3 |
| MATH 3318 | DIFFERENTIAL EQUATIONS | 3 |
| MATH 3321 | ABSTRACT ALGEBRA I | 3 |
| MATH 3330 | INTRODUCTION TO LINEAR ALGEBRA AND VECTOR SPACES | 3 |
| MATH 3335 | ANALYSIS I | 3 |
| MATH 3345 | NUMERICAL ANALYSIS AND COMPUTER APPLICATIONS | 3 |
| Additional upper level MATH or DATA 2000 level or above courses sufficient to complete 120 hours | 12 | |
| Total Hours | 120 | |
SUGGESTED COURSE SEQUENCE
Details of a personal course sequence should be made with the guidance of the Data Science undergraduate advisor, particularly since many courses are not offered every semester. For all entering freshmen, it is important to begin the mathematics sequence, starting with MATH 1426, Calculus I, in the first semester.
| First Year | |||
|---|---|---|---|
| Fall Semester | Hours | Spring Semester | Hours |
| MATH 1426 | 4 | ENGL 1301 | 3 |
| DATA 3401 | 4 | MATH 2425 | 4 |
| UNIV 1131 or UNIV-SC 1101 | 1 | DATA 3402 | 4 |
| BIOL 1441, CHEM 1441, PHYS 1443, or GEOL 1301 | 3-4 | BIOL 1442, CHEM 1442, PHYS 1444, or GEOL 1302 | 3-4 |
| Component Area Option (Suggested DATA 1301) | 3 | ||
| 15-16 | 14-15 | ||
| Second Year | |||
| Fall Semester | Hours | Spring Semester | Hours |
| Communication | 3 | Creative Arts | 3 |
| MATH 2326 | 3 | MATH 3300 | 3 |
| MATH 3330 | 3 | DATA 3421 | 4 |
| Component Area Option | 3 | DATA 3442 | 4 |
| DATA 3441 | 4 | ||
| 16 | 14 | ||
| Third Year | |||
| Fall Semester | Hours | Spring Semester | Hours |
| U.S. History (part 1) | 3 | U.S. History (part 2) | 3 |
| MATH 3313 | 3 | MATH 3300+ or DATA 2300+ | 3 |
| MATH 3345 | 3 | MATH 3302 | 3 |
| MATH 3321 | 3 | MATH 3335 | 3 |
| DATA 3461 | 4 | DATA 4380 | 3 |
| 16 | 15 | ||
| Fourth Year | |||
| Fall Semester | Hours | Spring Semester | Hours |
| Social & Behavioral Science | 3 | Language, Philosophy & Culture | 3 |
| MATH 3300+ or DATA 2300+ | 3 | Government/Political Science | 3 |
| MATH 3318 | 3 | DATA 4382 | 3 |
| Government/Political Science | 3 | MATH 3300+ or DATA 2300+ | 3 |
| DATA 4381 | 3 | MATH 3300+ or DATA 2300+ | 3 |
| 15 | 15 | ||
| Total Hours: 120-122 | |||
Advising Resources
Undergraduate and Graduate Advising
Location:
Life Science Building Room 206A and 206B
Email:
data.advising@uta.edu
Phone:
817-272-1512
Web:
Speak to an advisor in the Division of Data Science or schedule an appointment.