BSc in Business Analytics - Management in Newark United States | University of Delaware

As information technology progresses rapidly, the amount of data produced has grown exponentially in recent times. This data originates from diverse channels including digital transactions, mobile apps, sensor networks, video recording devices, and social platforms, reaching massive scales measured in terabytes or petabytes. Organizations now have significant potential to extract valuable operational and strategic insights through systematic data collection, processing, and analysis.

Program Learning Objectives 1. Utilize analytical techniques to enhance decision-making and data storytelling. 2. Design database structures aligned with business needs and interact with them using query languages. 3. Comprehend the complete machine learning pipeline along with fundamental supervised and unsupervised algorithms. 4. Participate in data acquisition, preprocessing, and governance processes. 5. Articulate confidently about implementing ML solutions for practical business challenges. 6. Acquire foundational competencies for adapting to emerging technologies. 7. Examine psychological and corporate aspects of ethical workplace conduct. Implement ethical frameworks to inform future choices. 8. Select suitable probability models for representing real-world scenarios. 9. Employ Bayesian computational methods to evaluate plausible data-generating models. 10. Present analytical findings through clear language and impactful visual representations. 11. Implement ML approaches for data examination. 12. Identify business scenarios where quantitative management methods are applicable. 13. Cultivate abilities for information collection, model development, and outcome interpretation to support choices. 14. Differentiate modeling approaches based on data characteristics: understanding constraints and appropriate applications of optimization, decision analysis, simulation, etc. 15. Evaluate challenges and propose actionable solutions using case information and analytical software. 16. Investigate how analytics informs corporate strategy. 17. Develop expertise in processing unorganized data with ML methods. 18. Create and execute causal analysis frameworks for key business determinations. 19. Address practical business issues using analytical modeling approaches.