Three basic data science concepts and their corresponding techniques are explored while emphasizing practical data handling and programming skills in Python: Sampling to estimate the properties of a population (Bootstrap), random assignment and experiments to make causal inferences (randomization test), and model selection to enable good predictions (cross-validation).