UMD’s MS in Business Analytics trains students to apply statistical methods, machine learning, and data visualization to real business challenges. The curriculum includes predictive modeling, data wrangling, optimization, and Python-based analytics tools. Students work on projects with corporate partners in finance, supply chain, marketing, and tech.
Customer segmentation using unsupervised clustering techniques
Sales forecasting model using time series data for retail chains
Fraud detection algorithm using ensemble learning on transaction logs
Optimization of warehouse distribution using linear programming
Churn prediction system for subscription-based mobile apps
Sentiment analysis of customer reviews across product categories
Forecasting airline ticket pricing with machine learning models
Real-time analytics dashboard for logistics performance monitoring
Building a recommendation engine for e-commerce platforms
Evaluating marketing campaign ROI using regression analysis
Risk modeling in credit scoring for financial institutions
Design of a KPI tracking system for executive dashboards
Customer lifetime value prediction using survival analysis
Pricing optimization strategies using conjoint analysis data
Social media influence mapping with graph analytics
Modeling the impact of economic indicators on sales pipeline
Machine learning model to detect anomalies in manufacturing data
Data visualization project using Tableau for retail insights
Optimizing advertisement spend allocation using A/B test results
Scenario modeling for business continuity planning under supply disruptions
Harness data to drive growth, efficiency, and innovation with real-world analytics projects in UMD’s Business Analytics MS.
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