MDST in Data Science
The proliferation of available data in industries such as marketing, government, education, health, science and technology (to name just a few) poses both challenges and opportunities. There is tremendous demand for skills such as data cleaning, analysis, and mining so that organizations can capitalize on the wealth of information contained in the data they have collected over the past few decades.
The field of Data Science requires skills from computer science, mathematics and design and, therefore, it is an ideal candidate for an MDST program. The ability to write programs to clean, access, and manipulate data, as well as the more advanced knowledge in machine learning and artificial intelligence techniques can be obtained through a solid background in Computer Science. From Mathematics, statistical modeling and analysis is obviously required, but a background in linear algebra can also be tremendously useful in terms of both modeling data and understanding many of the algorithms applied in machine learning. In order to present the knowledge gleaned from the data in an accessible and compelling way, information visualization (and hence the field of Design) is important.
Curriculum Requirements
Core 1 – Computer Science (28 credits)
| CSCI 161 | Intro to Programming I | 4 cr |
| CSCI 162 | Intro to Programming II | 4 cr |
| CSCI 362 | Data Structures | 4 cr |
| CSCI 366 | Database Systems | 4 cr |
| CSCI 450 | Artificial Intelligence | 4 cr |
| CSCI 452 | Data Mining | 4 cr |
| CSCI 453 | Large-Scale Data Analytics and Visualization | 4 cr |
Core 2 – Mathematics and Design (28 credits)
| CSCI 140 | Discrete Structures | 4 cr |
| MATH 161 | Calculus I | 4 cr |
| MATH 211 | Calculus II | 4 cr |
| MATH 235 | Survey of Statistics | 3 cr |
| MATH 236 | Elements of Statistics II | 3 cr |
| MATH 304 | Matrix Algebra and Applications | 4 cr |
| DESN 144 | Digital Theory and Skills | 3 cr |
| DESN 349 | Information Design | 3 cr |
Capstone
This can be fulfilled through an independent research project or thesis or through an co-op experience.
Required Related
Because domain knowledge is important for a Data Scientist, a minor in a field other than Mathematics or Computer Science is required so that students can apply their skills in a domain that is interesting and relevant for them. Their selection of a minor will inform and impact their capstone experience as well as assist them in obtaining a job in their chosen industry.