Bachelor of Science in Data Science (Statistics)
About This Program
The Bachelor of Science in Data Science Statistics concentration enhances theoretical and computational skills by blending advanced statistical methods with algorithm design and machine learning. Students gain a deeper understanding of the statistical 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, Statistics, and Data Science. 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. | 2 | |
| CALCULUS II | ||
| Data Science Specialization | ||
| DATA 3311 | MATHEMATICS FOR DATA SCIENCE | 3 |
| 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 |
| Statistics Specialization | ||
| MATH 2326 | CALCULUS III | 3 |
| MATH 3302 | MULTIVARIATE STATISTICAL METHODS | 3 |
| MATH 3313 | INTRODUCTION TO PROBABILITY | 3 |
| MATH 4311 | STOCHASTIC MODELS AND SIMULATION | 3 |
| or MATH 4312 | ACTUARIAL RISK ANALYSIS | |
| MATH 4313 | MATHEMATICAL STATISTICS | 3 |
| DATA 2301 | DATA VISUALIZATION & DATA STORYTELLING | 3 |
| DATA 4350 | INTRODUCTION TO TIME SERIES ANALYSIS | 3 |
| DATA 4351 | REGRESSION ANALYSIS | 3 |
| Select any three of the following courses. | 9 | |
| BIOSTATISTICS | ||
| BIOINFORMATICS | ||
| INTERMEDIATE STATISTICS FOR BUSINESS ANALYTICS | ||
| STATISTICS FOR EARTH AND ENVIRONMENTAL SCIENTISTS | ||
| OPERATIONS RESEARCH I | ||
| INTRODUCTION TO PROOFS | ||
| NUMERICAL ANALYSIS AND COMPUTER APPLICATIONS | ||
| STATISTICS IN PSYCHOLOGY | ||
Select a MATH or DATA course at 3000 level or higher. | ||
| Additional MATH at 3000 level or above or DATA 2000 level or above courses sufficient to complete 120 hours | 6 | |
| 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 |
| Component Area Option (Suggested DATA 1301) | 3 | Life & Physical Science Sequence | 3-4 |
| Life & Physical Science Sequence | 3-4 | ||
| 15-16 | 14-15 | ||
| Second Year | |||
| Fall Semester | Hours | Spring Semester | Hours |
| Communication | 3 | Creative Arts | 3 |
| U.S. History (part 1) | 3 | U.S. History (part 2) | 3 |
| MATH 2326 | 3 | Language, Philosophy, Culture | 3 |
| DATA 2301 | 3 | DATA 3311 | 3 |
| DATA 3421 | 4 | DATA 3441 | 4 |
| 16 | 16 | ||
| Third Year | |||
| Fall Semester | Hours | Spring Semester | Hours |
| MATH 3313 | 3 | MATH 3302 | 3 |
| DATA 3442 | 4 | MATH 4311 or 4312 | 3 |
| DATA 3461 | 4 | MATH 4313 | 3 |
| Government/Political Science | 3 | DATA 4380 | 3 |
| Government/Political Science | 3 | ||
| 14 | 15 | ||
| Fourth Year | |||
| Fall Semester | Hours | Spring Semester | Hours |
| Social & Behavioral | 3 | DATA 4382 | 3 |
| Approved Elective | 3 | MATH or DATA Elective | 3 |
| DATA 4350 | 3 | MATH or DATA Elective | 3 |
| DATA 4351 | 3 | Approved Elective | 3 |
| DATA 4381 | 3 | Approved Elective | 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.