Data-driven Modelling
- Introduction to modeling and data analytics
- Descriptive analytics (what is happening?)
- Cross-sectional data, time series, panel data
- Data pre-processing (cleaning, integration, and reduction)
- Introduction to data visualization (definition, methods, and tools)
- Predictive analytics (what will likely happen?)
- Supervised learning
- Prediction of qualitative variables
- Prediction of quantitative variables
- Regression models
- Violation of the classical assumptions
- Dynamic regression models
- Extension to panel data
- Overview of unsupervised learning
- Prescriptive analytics (what should we do?)
- Overview of mathematical programming and convex optimization
- ?Data-driven uncertainty set design
- Data-driven robust optimization
- Data-driven inverse optimization
- Real-world applications
- Introduction to software (python+pyomo)