Statistics and Data Science (BSSDS)
The Bachelor of Science in Statistics and Data Science (SDS) provides students with foundational training and marketable skills in statistics and data science. The curriculum is designed to equip students to execute all stages of a data analysis, from data acquisition and exploration to application of statistics and machine learning methods to the creation of data products (e.g, reports, apps, dashboards). Throughout the program, students are exposed to the principles of and tools for conducting reproducible data science and are taught to think critically about relevant ethical and legal issues (e.g., data privacy, algorithmic bias, misrepresentation of findings). The program prepares students to enter the workforce directly, or after pursuing specialized graduate training, as statisticians and data scientists or in other roles where training in these fields is excellent preparation.
Total Hours Required: 120
Plan of Study
The Plan of Study is a suggested four-year course sequence to support academic planning and serves as a helpful guide. Currently enrolled students should meet with their academic advisor to tailor their course selections and timelines to their individual goals and circumstances.
| Year 1 | ||
|---|---|---|
| Semester 1 | Hours | |
| SDS 313 | Introduction to Data Science | 3 |
| Hours chosen from: | 4 | |
| Differential and Integral Calculus | ||
| Differential Calculus | ||
| Differential Calculus for Science | ||
| RHE 306 | Rhetoric and Writing | 3 |
| First-Year Signature Course (090) | 3 | |
| Free Elective | 3 | |
| Hours | 16 | |
| Semester 2 | ||
| C S 303E | Elements of Computers and Programming | 3 |
| Hours chosen from: | 4 | |
| Sequences, Series, and Multivariable Calculus | ||
| Integral Calculus | ||
| Integral Calculus for Science | ||
| SDS 315 | Statistical Thinking | 3 |
| U.S. History (060) | 3 | |
| Natural Science and Technology, Part I (030) | 3 | |
| Hours | 16 | |
| Year 2 | ||
| Semester 1 | ||
| SDS 431 | Probability and Statistical Inference | 4 |
| M 340L or M 341 |
Matrices and Matrix Calculations or Linear Algebra and Matrix Theory |
3 |
| Lower-division breadth course | 3 | |
| American and Texas Government (070) | 3 | |
| Humanities (040) | 3 | |
| Hours | 16 | |
| Semester 2 | ||
| SDS 334 | Intermediate Statistical Methods | 3 |
| Lower-division breadth course | 3 | |
| U.S. History (060) | 3 | |
| Natural Science and Technology, Part I (030) | 3 | |
| C S 313E | Elements of Software Design | 3 |
| Hours | 15 | |
| Year 3 | ||
| Semester 1 | ||
| SDS 336 | Practical Machine Learning | 3 |
| C S 327E | Elements of Databases | 3 |
| Upper-division breadth course | 3 | |
| American and Texas Government (070) | 3 | |
| Free Elective | 3 | |
| Hours | 15 | |
| Semester 2 | ||
| Hours chosen from: SDS | 3 | |
| Upper-division breadth course | 3 | |
| Free Elective | 3 | |
| Visual and Performing Arts (050) | 3 | |
| Free Elective | 3 | |
| Hours | 15 | |
| Year 4 | ||
| Semester 1 | ||
| SDS 354 | Advanced Statistical Methods | 3 |
| Hours chosen from: SDS | 3 | |
| Social and Behavioral Sciences (080) | 3 | |
| Free Elective | 3 | |
| Free Elective | 3 | |
| Hours | 15 | |
| Semester 2 | ||
| SDS 357 | Case Studies in Data Science | 3 |
| Free Elective | 3 | |
| Free Elective | 3 | |
| Free Elective | 3 | |
| Hours | 12 | |
| Total Hours | 120 | |
Requirements
All requirements are listed below, starting with the most specialized moving to the most general. Additional requirements may follow the table, so be sure to read the entire page. Some required courses listed below may also satisfy General Education requirements, including Core Curriculum.
| Code | Title | Hours |
|---|---|---|
| Major | ||
| Hours chosen from: | 14 | |
| Matrices and Matrix Calculations | ||
or M 341 | Linear Algebra and Matrix Theory | |
| Elements of Computers and Programming (or equivalent C S course) | ||
or C S 312 | Introduction to Programming | |
| Elements of Databases (or equivalent C S course) | ||
Sequence 1: | ||
| Differential and Integral Calculus | ||
| Sequences, Series, and Multivariable Calculus | ||
Sequence 2: | ||
| Differential Calculus | ||
| Integral Calculus | ||
| Multivariable Calculus | ||
| Sequence 3: | ||
| Differential Calculus for Science | ||
| Integral Calculus for Science | ||
| Multivariable Calculus | ||
| Subtotal | 14 | |
| Degree (see details below) | 40 | |
| Free electives: Additional coursework to reach total hours required. | 24 | |
| Subtotal | 64 | |
| General Education | ||
| Core Curriculum | 42 | |
| Foreign Language other than English, Beginning Proficiency | ||
| Subtotal | 42 | |
| College Requirements - Natural Sciences | ||
| General University Requirements | ||
| Total Hours | 120 | |
Degree-Bachelor of Science in Statistics Data Science (BSSDS)
| Code | Title | Hours |
|---|---|---|
| Degree | ||
| SDS Breadth Requirement | ||
| Hours chosen from: In a single field of study other than SDS; at least six upper-division hours | 12 | |
| Statistics and Data Sciences | ||
| SDS 313 | Introduction to Data Science | 3 |
| SDS 315 | Statistical Thinking | 3 |
| SDS 431 | Probability and Statistical Inference | 4 |
| SDS 334 | Intermediate Statistical Methods | 3 |
| SDS 336 | Practical Machine Learning | 3 |
| SDS 354 | Advanced Statistical Methods | 3 |
| SDS 357 | Case Studies in Data Science | 3 |
| Hours chosen from: | 6 | |
| Bayesian Statistics | ||
| Data Visualization | ||
| Statistical Theory | ||
| Time Series Forecasting | ||
| Please see department website for a full list. https://stat.utexas.edu/academics/undergraduate-major | ||
| Total Hours | 40 | |
Additional Requirements and Policies
- At least 21 hours of upper-division course work in Statistics and Data Sciences must be completed in residence at the university.
- Students must fulfill both the University's general requirements for graduation and the college requirements.
- They must also earn a grade of at least C- in all courses required for the major, and a grade point average in these courses of at least 2.00.
- More information about grades and the grade point average is given in the General Information Catalog.