BS Data Science

The Data Science program prepares students for professional careers and graduate study by mastering mathematics, statistics, computer science, and core data science concepts such as machine learning, deep learning, and data mining as guided by the 2021 ACM Computing Competencies for Undergraduate Data Science Curricula. The program provides the key preparation for a career as a data scientist, data analyst, data engineer, business analyst, marketing analyst, data architect, data and analytic manager, business intelligence analyst, data mining analyst, or machine learning engineer.

Data Scientists are typically involved with designing data modeling processes and creating algorithms and predictive models to extract the information needed by an organization to solve complex problems. Data analysts examine large datasets to identify trends, develop charts, and create visual presentations to help businesses make more strategic decisions. There are several titles for data analysts, including but not limited to database analyst, business analyst, market research.

Program Educational Objectives:

Five years after completing the Data Science program, students will: 

1. Apply computing, mathematical, and statistical skills, practical tools, and techniques in data science to solve real-world problems to facilitate successful careers in data science and related fields.  
2. Demonstrate the ability to communicate effectively and professionally, individually and in team environments, with colleagues and clients of varying backgrounds.  
3. Demonstrate an ability to improve and expand career skills through graduate studies, continuing self-directed learning, and professional development
   
    

Graduates of the program will have the ability to:

1. Analyze a complex computing problem and apply principles of computing and other relevant disciplines to identify solutions.
2. Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline.
3. Communicate effectively in a variety of professional contexts.
4. Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.
5. Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline.
6. Apply theory, techniques, and tools throughout the data analysis lifecycle and employ the resulting knowledge to satisfy stakeholders’ needs.