Joel Grus ■■ Get a crash course in Python ■■ Learn the basics of linear algebra, statistics, and probability— and understand how and when they're used in data science ■■ Collect, explore, clean, munge, and manipulate data ■■ Dive into the fundamentals of machine learning ■■ Implement models such as k-nearest neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering ■■ Explore recommender systems, natural language processing, network analysis, MapReduce, and databases