Computing for Data Science


Stanford School of Humanities and Sciences



This course provides a practical introduction to modern techniques for computing with data, teaching advanced use of the R system and explores connections to other key software tools. A key challenge with data computing is how to work efficiently by choosing the best programming approach for each stage of a project. Students learn and practice the use of R for serious applications and substantial projects. The examples in this course are motivated by actual problems in the field. Therefore, students gain knowledge of many different tools that can be combined to solve real problems. The final project will use an R package, based on a student’s own work or research.

Limited enrollment! Due to the limited space in this course, interested students should enroll as soon as possible.


Programming experience including familiarity with R; computing at least at the level of CS106; statistics at the level of STATS110 or STATS141. Complete STATS202 or STATS216 with a grade of B+ or better.

Topics include

  • Programming and computing techniques for data science
  • Acquisition and organization of data
  • Visualization,modelling and inference for scientific applications
  • Presentation and interactive communication of results

Note on Course Availability

The course schedule is displayed for planning purposes – courses can be modified, changed, or cancelled. Course availability will be considered finalized on the first day of open enrollment. For quarterly enrollment dates, please refer to our graduate certificate homepage.

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