Data Science - BS
Our data science major curriculum intentionally provides a foundation and pathway for engaging broad discipline interests in the arts, humanities, social sciences, physical sciences, health sciences, and business. Data - in any domain - is at our disposal almost instantaneously. We need the knowledge and skills to manage, analyze, summarize and interpret the data, and then be able to effectively communicate, both visually and verbally, the results in context within an ethical and respectful frame.
This major is offered in the College for Women only.
| Code | Title | Credits |
|---|---|---|
| Required Prerequisite Courses | ||
| CSCI 1110 | Introduction to Computer Science | 4 |
| MATH 1130 | Calculus I | 4 |
| STAT 1090 | Statistical Analysis | 4 |
| Required Major Courses | ||
| DSCI 1000 | Telling Stories with Data - Introduction to Data Visualization | 4 |
| DSCI 2100 | Introduction to Programming: Applied Computing I | 4 |
| DSCI 3000W | AI Data Ethics, Governance & Social Impact | 4 |
| DSCI 3100 | Database Management | 4 |
| DSCI 3200W | Analyzing Social Issues with Data | 4 |
| DSCI 3300 | Introduction to Machine Learning for Data Science | 4 |
| DSCI 4100 | Introduction to Cloud Computing | 4 |
| DSCI 4200 | Introduction to Large Language Models: A Machine Learning Approach | 4 |
| DSCI 4952 | Independent Study | 2-4 |
| or DSCI 4604 | Internship | |
| Interdisciplinary Track Electives 1 | 16 | |
| Required Supporting Courses | ||
| CSCI 1120 | Algorithms and Java Programming | 4 |
| MATH 1140 | Calculus II | 4 |
| STAT 2090 | Statistical Modeling | 4 |
| STAT 3090 | Predictive Analysis | 4 |
| Additional DSCI Elective | 4 | |
| Total Credits | 82-84 | |
- 1
Suggested interdisciplinary tracks include Business Administration, Economics, Sociology, Psychology, and Arts and Humanities. Students are encouraged to consult with their academic advisor to explore different pathways that best suit their individual goals.
Data science majors satisfy the Writing Requirement for Majors by completing DSCI 3000W AI Data Ethics, Governance & Social Impact and DSCI 3200W Analyzing Social Issues with Data. They complete the liberal arts core Writing Requirement with two other writing-intensive courses (CORE 1000W The Reflective Woman and CORE 3990W Global Search for Justice).
| Freshman | |||
|---|---|---|---|
| Fall | Credits | Spring | Credits |
| DSCI 1000 | 4 | CSCI 1110 | 4 |
| MATH 1130 | 4 | STAT 1090 | 4 |
| Core Courses, as needed | MATH 1140 | 4 | |
| Core Courses, as needed | |||
| 8 | 12 | ||
| Sophomore | |||
| Fall | Credits | Spring | Credits |
| DSCI 3000W | 4 | DSCI 2100 | 4 |
| CSCI 1120 | 4 | DSCI 3300 | 4 |
| Core Courses, as needed | Core Courses, as needed | ||
| 8 | 8 | ||
| Junior | |||
| Fall | Credits | Spring | Credits |
| DSCI 3100 | 4 | STAT 3090 | 4 |
| STAT 2090 | 4 | DSCI 4200 | 4 |
| Interdisciplinary Elective | 4 | DSCI 3200W | 4 |
| Interdisciplinary Elective | 4 | ||
| 12 | 16 | ||
| Senior | |||
| Fall | Credits | Spring | Credits |
| DSCI 4100 | 4 | DSCI 4604 or 4952 | 2-4 |
| Data Science Elective | 4 | Interdisciplinary Elective | 4 |
| Interdisciplinary Elective | 4 | ||
| 12 | 6-8 | ||
| Total Credits: 82-84 | |||