Data Science Minor
The Data Science Minor prepares students with the theory and skills necessary to analyze and derive insights from large data sets. The curriculum includes techniques from mathematics (particularly statistics) and computer science. It encompasses academic topics including machine learning, cluster analysis, data mining, and data visualization.
Goal 1: Students will be prepared for a variety of professions in Data Science and/or Master’s degree programs in Data Science and be able to adapt to complex technological and analytical environments in the workplace.
Objective 1.1: Students will be proficient programming in Python.
Objective 1.2: Students will be able to analyze data sets using a variety of software and analytical approaches.
Objective 1.3: Students will be able to communicate the results of technical data analysis in a manner that is understandable to non-specialists.
| Code | Title | Hours |
|---|---|---|
| The Minor in Data Science will require completion of a total of six (6) courses as outlined below: | ||
| Three (3) Core Courses: | ||
| DSC 223 | Intro Math of Data Science | 3 |
| CSC 133 | Python Programming for All | 3 |
| or CSC 115 | Intro to Computer Science | |
| DSC 325 | Essentials of Data Science | 3 |
| or CSC 346 | Introduction to Data Science | |
| Three (3) Elective Courses (select from the list below; at least one must be a DSC, CSC or MAT course): | ||
| CSC 134 | Databases for All | 3 |
| or CSC 351 | Database Management Systems | |
| CSC 132 | Artificial Intellig for All | 3 |
| or CSC 362 | Artificial Intelligence | |
| CSC 342 | Computer Vision | 3 |
| CSC 345 | Image Data Science | 3 |
| CSC 348 | Advanced Machine Learning | 3 |
| CSC 353 | Internet Application Develpmnt | 3 |
| CSC 358 | Big Data and Web Intlgce | 3 |
| CSC 362 | Artificial Intelligence | 3 |
| MAT 311 | Numerical Analysis | 3 |
| MAT 313 | Mathematical Optimization | 3 |
| MAT 316 | Operations Research | 3 |
| MAT 322 | Mathematical Statistics | 3 |
| MAT 328 | Design of Experiments | 3 |
| MAT 420 | Convex Analysis | 3 |
| MAT 423 | Applied Statistical Methods | 3 |
| MAT 424 | Regression and Time Series | 3 |
| DSC 326 | Advanced Data Science | 3 |
| or CSC 347 | Advanced Data Science | |
| DSC 425 | Machine Learning/Data Science | 3 |
| ECN 410 | Econometrics | 3 |
| ECN 415 | Economic Forecasting | 3 |
| ECN 487 | Research Methods | 3 |
| DSS 415 | Data Wrangling & Visualization | 3 |
| DSS 416 | Data Wrangling: Ethics Int. | 3 |
| DSS 420 | Introduction to Data Mining | 3 |
| DSS 435 | Advanced Business Analytics | 3 |
| DSS 445 | Statistical Programming Lang | 3 |
| DSS 451 | Machine Learning for Bus I | 3 |
| DSS 455 | Machine Learning for Bus II | 3 |
| BIO 420 | Bioinformatics | 4 |
| BIO 420L | Bioinformatics Lab | 0 |
| INT 270 | Special Topics | 1-3 |
| Any internship course (in any department) that is pre-approved as having sufficient data science content. | 3 | |