Applied Data Science

← Back to document page

Applied data ScienceIan LangmoreDaniel Krasner2ContentsI Programming Prerequisites11 History and Culture . . . . . . . . . . . . . . . . . . . . . . . The Shell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Streams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . streams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Text.

tatistical knowledge and teach them software development fundamentals3. This course will cover Design of small software packages Working in a Unix environment Designing software in teams Fundamental statistical algorithms such as linear and logistic regres-sion 3Our view of what constitutes the necessary fundamentals is strongly in uenced by the

  Design, Data, Sciences, Fundamentals, Data science