CMDA-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: 2
Average GPA: 3.25 (B+)
Strict A Rate (No A-) : 30.53%
Average Withdrawal Rate: 8.33%
| Ali Habibnia | 2024 | 58.3% | 15.3% | 12.5% | 0.0% | 5.5% | 8.3% | 3.26 | 2 |