Python reasoning
Get comfortable with variables, lists, functions and basic debugging before combining them into a data workflow.
Working with data
Practice inspecting a dataset, identifying missing values and explaining what each column means.
Evaluation habits
Keep the data used for evaluating your model separate from its training data. Ask what good performance means for your actual problem.
