The program is grounded in the principles of ethical data practices and leadership, emphasizing the ability to create opportunities that leverage data for positive impact. This comprehensive approach ensures that graduates are well-versed in data manipulation, analysis, and visualization, possessing the skills to address complex challenges in today’s data-driven world.

Students in the Bachelor of Science in Data Science program gain hands-on experience in applying data science skills to develop innovative solutions. They become proficient in using tools such as SQL, Power BI, and Python, enabling them to extract insights, apply cutting edge analyses, and make data-driven decisions. Students have the opportunity to apply their skills in real-world scenarios, combining data analysis with entrepreneurial thinking.

• Apply entrepreneurial thinking, leadership, and data science skills to identify, analyze, and address global challenges and opportunities, leading self and others toward innovative solutions.
• Illustrate the process of new venture creation.
• Apply quantitative methods to analyze and solve complex problems.
• Apply critical and ethical thinking across different domains of knowledge, demonstrating strong written, oral, and technology based communication skills.
• Demonstrate proficiency in data manipulation, statistics, and data modeling using tools such as SQL, Power BI, and Python.
• Showcase the ability to clean, analyze, and visualize data effectively, and construct efficient data-driven models.
• Create a portfolio that showcases career-ready work, reflecting current knowledge and practice in data science.

The Bachelor of Science in Data Science requires the completion of 120 credits. The degree program is designed to be taken in a full-time, year-round manner, allowing it to be completed in three (3) years. However, this duration may vary depending on individual course progression and any prior credits transferred. The time limit for completing the degree program is eight (8) years.

The Bachelor of Science in Data Science is comprised of three content areas: general education courses (36 semester credits); data science and software engineering courses (57 semester credits); and entrepreneurship courses (27 semester credits).

Students must successfully complete all required courses with a passing grade.

As part of students’ fulfillment of their degree requirements, they are required to assemble and defend a portfolio of work in DS 440 Portfolio Review. The learning outcomes for this are to:

1. Present, reflect, and iterate on a portfolio of data science challenges and solutions which demonstrate career readiness.
2. Create a resume that demonstrates career readiness.
3. Exhibit entry-level readiness by completing tasks related to SQL database management, Phyton data analysis using Pandas, data visualization with Power BI, database manipulation, data analysis, and the creation of insightful visualizations.
4. Exhibit entry-level career readiness by demonstrating machine learning proficiency, emphasizing regression, classification, interpretation of model parameters, evaluation metrics and the application of algorithms including linear regression, logistic regression, decision trees, random forests, and support vector machines.