Level UP-Clustering of Covid data (part 1 of 2)

positions available: 1 The 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-Clustering of Covid data (part 2 of 2)

positions available: 1 The student will apply decision trees to explain the COVID data clustering. The student will interpret the results and write a report.

Level UP-Analyzing factors that cause Car speeding Phase 1

positions available: 2 This analysis used data from speed zones and traffic signs using methods such as functional data clustering algorithms. In this project, we will 1. Determine indicators associated with a car speeding such as known police zones, how enforcement is done in these areas and unknown information about the day (weather, holiday, sporting events) that may or may not affect the data. 2. Apply functional data clustering and model-based clustering algorithms

Level UP-Analyzing factors that cause Car speeding Phase 2

positions available: 2 This analysis used data from speed zones and traffic signs using methods such as functional data clustering algorithms. In this project, we will 1. Determine indicators associated with a car speeding such as known police zones, how enforcement is done in these areas and unknown information about the day (weather, holiday, sporting events) that may or may not affect the data. 2. Apply functional data clustering and model-based clustering algorithms