Practical and Marketable Skills. Introduction to programming languages (e.g., R/Python) commonly used in applications of data science, and practical data skills: collecting, scraping, cleaning, merging, processing, and visualizing data, descriptive analysis, optimization, and supervised/unsupervised statistical learning. Synergy, Application, and Experience. Gain … Read more