Introduction to Python programming in interesting, relevant, and practical contexts for data science, such as data visualization, central tendency, hypothesis testing, sampling distributions, estimation, ANOVA, Chi-Squared Test, correlation, and regression. Basic programming skills are developed to explore and analyze data from multiple disciplines. Fundamental programming constructs: iteration, conditional statements, built-in data structures, input and output, and functions.