The University of Texas at Austin College of Natural Sciences 19 courses 15 total credits
The minor in Statistics and Data Science will give students experience manipulating, summarizing and visualizing data and applying statistical and machine learning methods. Students are exposed to the principles of and tools for conducting reproducible data analysis and are taught to think critically about relevant ethical issues (e.g., data privacy, misrepresentation of findings). Requirements are listed in the table below. 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. Students should also review the University's Undergraduate Minor and Certificate Requirements and Policies.
| College Requirements - Natural Sciences | credits |
| Undergraduate Minor and Certificate Requirements and Policies | credits |
Foundational Area Courses
Statistics:
| Code | Course Title | Credits |
|---|---|---|
| SDS 320E | Elements of Statistics | 3 |
| SDS 320H | Elements of Statistics: Honors | 3 |
| SDS 315 | Statistical Thinking | 3 |
| Total Foundational Area Courses | 3 credits | |
Foundational Area Courses
Data Science:
| Code | Course Title | Credits |
|---|---|---|
| SDS 322E | Elements of Data Science | 3 |
| SDS 313 | Introduction to Data Science | 3 |
| Total Foundational Area Courses | 3 credits | |
Foundational Area Courses
Programming: (credit earned through Credit by Examination (CBE) or transfer coursework with a letter grade of C- or better may be used to satisfy this requirement)
| Code | Course Title | Credits |
|---|---|---|
| C S 303E | Elements of Computers and Programming | 3 |
| C S 312 | Introduction to Programming | 3 |
| C S 312H | Introduction to Programming: Honors | 3 |
| Total Foundational Area Courses | 3 credits | |
Supplementary Courses and Areas
Regression/Modeling:
| Code | Course Title | Credits |
|---|---|---|
| SDS 324E | Elements of Regression Analysis | 3 |
| SDS 334 | Intermediate Statistical Methods | 3 |
| STA 372T.21 | Time Series Forecasting | 3 |
Supplementary Courses and Areas
Machine Learning:
| Code | Course Title | Credits |
|---|---|---|
| SDS 326E | Elements of Statistical Machine Learning | 3 |
| SDS 336 | Practical Machine Learning | 3 |
Supplementary Courses and Areas
Databases:
| Code | Course Title | Credits |
|---|---|---|
| C S 327E | Elements of Databases | 3 |
Supplementary Courses and Areas
Probability/Mathematical Statistics/Statistical Inference:
| Code | Course Title | Credits |
|---|---|---|
| SDS 321 | Introduction to Probability and Statistics | 3 |
| SDS 431 | Probability and Statistical Inference | 4 |
| M 362K | Probability I | 3 |
| M 378K | Introduction to Mathematical Statistics | 3 |
Supplementary Courses and Areas
Data Visualization:
| Code | Course Title | Credits |
|---|---|---|
| SDS 366 | Data Visualization | 3 |
Click a course code or title to read the full course description.
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