Ds100.org Website Review

Combining data, computation, and inferential thinking, data science is redefining how people and organizations solve challenging problems and statistics courses as well as methods courses in other fields. In this clas*, we explore key areas of data science including question formulation, data collection and cleaning, visualization, statistical inference, predictive modeling, and decision making.​ Through a strong emphasizes on data centric computing, quantitative critical thinking, and exploratory data an*lysis this clas* covers key principles and techniques of data science. These include languages for transforming, querying and an*lyzing data; algorithms for machine learning methods including regression, clas*ification and clustering; principles behind creating informative data visualizations; statistical concepts of measurement error and prediction; and techniques for scalable data processing. ENABLE students to start careers as data scientists by providing experience working with real-world data, tools, and techniques EMPOWER students to apply computational and inferential thinking to tackle real-world problems While we are working to make this clas* widely accessible we currently require the following (or equivalent) prerequisites: provides basic exposure to python programming and working with tabular data as well as visualization, statistics, and machine learning. some basic concepts like linear operators and derivatives to enable statistical inference and derive new prediction algorithms. This may