In the capstone, students will engage on a real world project requiring them to apply skills from the entire data science pipeline: preparing, organizing, and transforming data, constructing a model, and evaluating results. Through a collaboration with Coursolve, each Capstone project is associated with partner stakeholders who have a vested interest in your results and are eager to deploy them in practice. These projects will not be straightforward and the outcome is not prescribed -- you will need to tolerate ambiguity and negative results! But we believe the experience will be rewarding and will better prepare you for data science projects in practice.
Project A: Blight Fight
In this project, you will build a model to predict when a building is likely to be condemned. The data is real, the problem is real, and the impact is real.
Week 2: Derive a list of buildings
You are given sets of incidents with location information; you need to use some assumptions to group these incidents by location to identify specific buildings.
Week 3: Construct a training dataset
Construct a training set by associating each of your buildings with a ground truth label derived from the permit data.
Week 4: Train and evaluate a simple model
Use a trivial feature set to train and evaluate a simple model
Week 5: Feature Engineering
Derive additional features and retrain to improve the efficacy of your model.