Optimization methods for agriculture insurance
This project is an application of mathematical modelling and optimization to a livestock insurance problem. The goal is to analyze various scenarios from a farmer’s perspective and to minimize the loss. The main idea is to design and implement in Python a numerical simulation, including various scenarios in terms of the farm size and insurance premiums.
Numerical analysis with Python (part 3 of 3)
The student will write and test Python code for the labs for Numerical Analysis
Level Up Influence of COVID pandemic on the stock market Part I
Develop the time series framework and study the evolution of the Amazon stock and the influence of the pandemic
Level UP-Analyzing factors impacting COVID-19 vaccination rates
positions available: 3This analysis used COVID-19 vaccination data, and country indicators from the World Bank to 1. Determine indicators that are associated with vaccination rate2. Create indices to measure the Vaccine Utilization and Vaccination Motivation per country3. Apply Decision trees and Pearson correlations to determine relationships with country indicators and these indices
Level Up Influence of COVID pandemic on the stock market Part II
Do a time series intervention analysis for tech, energy, financial, and transportation companies and compare the evolution during the pandemic.
Level UP-Prediction of functional COVID data
positions available: 2The students will implement the KNN algorithm for Covid data in Python based on existing libraries.
Level UP- Numerical analysis with Python(part 1 of 3)
positions available: 1The student will write Python code for the labs for Numerical Analysis
Level Up Exploring the relationship between oil prices and exchange rates
Do a time series analysis to analyze the relationship between gas prices and CAD/USD exchange rate.
Level UP-Clustering of Covid data (part 1 of 2)
positions available: 1The students will clean the Covid data collected from OUR WORLD in DATA and implement a clustering algorithm for Covid data in R based on existing libraries.
Level UP-Writing-testing a R package on clustering functional data (part 1 of 2)
positions available: 2One student will write R/C code for the T-funHDDC algorithm for clustering functional data with outliers.The second student will do the testing.
Level UP-Clustering of Covid data (part 2 of 2)
positions available: 1The student will apply decision trees to explain the COVID data clustering. The student will interpret the results and write a report.
Level UP- Numerical analysis with Python(part 2 of 3)
positions available: 1The student will write Python code for the labs for Numerical Analysis
Level UP-Writing-testing a R package on clustering functional data (part 2 of 2)
positions available: 1The student will write R/C code for the T-funHDDC algorithm for clustering functional data with outliers and the package manual.