Professor Widom offers a range of options for different audiences, although the focus is on fundamental learning rather than advanced development skills or operational deployment. Material is drawn from a course she developed at Stanford. The most detailed offering is a short-course lasting up to a full week, covering a variety of topics and including a great deal of hands-on learning. Except for the general overview, students should be comfortable with basic mathematical concepts, and some portions of the material require a modest amount of computer programming experience (equivalent to an introductory programming course).

Many of the world's biggest discoveries and decisions in science, technology, business, medicine, politics, and society as a whole, are now being made on the basis of analyzing data. Professor Widom's seminars, tutorials, and short-courses provide an introduction to big data and data science, including some history, case studies, and common pitfalls, along with broad hands-on coverage of tools & techniques for data collection, analysis, and visualization.



Formats range from 2 hour seminars, to 1-2 day tutorials, to a weeklong course. Depending on the desired format and the background of the students, the following topics may be covered.


Introduction to Big Data and Data Science

  • Motivation, history, and terminology

  • Success stories and failure cases

  • Privacy considerations

Fundamental Concepts and Techniques

  • Basic data manipulation and analysis

  • Machine learning: regression, classification, clustering

  • Data mining

  • Network analysis and unstructured data

Tools for Data Manipulation and Analysis

  • Spreadsheets

  • Data visualization tools

  • Relational databases and SQL

  • The Python and R programming languages

  • Jupyter notebooks