exam based Kaggle case study

Hi Everyone,

I’ll have an exam based on this case study: Costa Rican Household Poverty Level Prediction | Kaggle

In the exam less data will be provided: about 10 attributes [columns] and about 1000 data objects [rows]. Some attributes are slightly different encoded.

However, the objective is the same: Try to identify households, which live in poverty and need social welfare assistance.

As I’m stuck and don’t know how to start exactly.

Basically, my confusion comes - on which nodes exactly to use, which model (KNN, Decision Tree, etc…)

Also, when and how to use the training and test data?

If someone can give some hints on what nodes and and models to use in: data preparation, evaluation, modeling and deployment will be great.

Any help is highly appreciated!