ENGM 204: Data Analytics Project Lab (DAPL)
This class is held in the spring and shows students how data analytics, machine learning, and artificial intelligence create value for organizations. The proliferation of IT-mediated economic activity generates an abundance of micro-level market data which has led to the competitive use of analytics, experimentation, and fact-based decision-making. Today, most organizations rely extensively on data analysis to predict outcomes and guide executive decision-making.
DAPL provides a great opportunity for students to work on a real question and gain access to talented engineers who understand business by matching student teams with a business challenge involving analytics and machine learning. Projects are sourced from both commercial and non-profit as well as government organizations. The ideal project has a reasonable chance of a valuable outcome for the company and a large enough data set (at least 50,000) sufficient for training AI and ML models.
- Add real-time social media data to existing data assets; build a model to identify the likelihood that legislation would pass into law.
- Analyze price elasticities across complex consumer goods product lines to make pricing recommendations and focus offerings by eliminating unprofitable segments.
- Apply machine learning to expense forecasting for complex multi-billion-dollar division and significantly improve accuracy and demonstrated potential to dramatically reduce analyst labor.