ECON-4314: Big Data Economics
Description: Applied econometrics dealing with big data. Theoretical, computational, and statistical underpinnings of big data analysis. The use of econometric models and deep machine learning algorithms to analyze the high-dimensional data sets. Implications in research focusing on economic questions that arise from rapid changes in data availability and computational technology. Materials are hands-on tutorials that come with Python codes and real-world data sets.
Pathways: N/A
Course Hours: 3 credits
Sections Taught: 4
Average GPA: 2.81 (B)
Strict A Rate (No A-) : 22.03%
Average Withdrawal Rate: 4.58%
| Ali Habibnia | 2024 | 31.1% | 47.0% | 4.5% | 0.0% | 17.4% | 0.0% | 2.65 | 2 |
| Bo Zhou | 2023 | 39.1% | 23.3% | 23.3% | 0.0% | 5.0% | 9.2% | 2.98 | 2 |