Data Analysis
Machine Learning for Econometrics
Use prediction thoughtfully, cross-validate with discipline, and connect ML outputs to causal questions carefully.
Tree-based models and regularised regressions appear as tools, not magic. Participants practice leakage avoidance and humility when exporting predictions to structural discussions.
- Format
- Blended cohort
- Duration
- 7 weeks · blended
- Level
- Intermediate
- Software
- Python, R
- Topic
- Machine learning
- Tuition
- 12,100 THB · informational until admissions confirms
What is included
- Leakage checklist labs
- Cross-validation discipline for time splits
- Interpretability methods with honest limits
- Bridge exercises from prediction to policy questions
Outcomes you can evidence
- Run CV that respects temporal structure
- Explain feature importance without fairy tales
- State when ML is decoration versus decision support
Lead contact
Nattapol Siri
Applied ML lead bridging data science and econometrics teams.
Participant voices
Machine Learning for Econometrics — leakage checklist caught a split bug our DS team missed.
Questions we expect
Ready to talk fit?
Request information Admissions responds with prerequisites and employer letter options.