Professor Widom offers a range of options for different audiences, with a focus on fundamental learning rather than advanced development skills or operational deployment. Material is drawn from an introductory data science course she developed at Stanford. Short-courses can last 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 short-courses provide an introduction to data science, including some history, case studies, and common pitfalls, along with broad, interactive, hands-on coverage of tools & techniques for data collection, analysis, and visualization.
TOPICS
Formats can range from a 2-hour overview to a weeklong course, or anything in between. Depending on the time allotted and the background of the students, the following topics may be covered.
Introduction to 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