Connectors are one or two-unit courses which give students an in-depth introduction into the use of the data science toolkit and concepts in a particular field. Connector courses vary every semester, but are usually within the domain of social sciences. Connectors are not an official part of Data 8, though they play a crucial role in the data science education ecosystem with the DSEP (Data Science Education Program). Students are encouraged to take them together with Data 8 or a semester after they take Data 8.
For more information about connector courses, check out The Data Science Connector Courses Page.
We have also created a webpage to interact with some of our featured connectors on the Connectors Showcase Page.
Modules are short explorations into data science that can be implemented into (almost) any class on campus. Modules allow students to explore a data set relevant to their course with the help of the data science toolkit.
Like connectors, modules vary widely, and can be customized to fit each instructor’s need and objective for the course. A module might include one or two lectures on analyzing course-relevant data and learning how to interpret the graphs, or they can be a set of labs in which students will learn the basics of programming and statistics which they can apply to their field of studies. Some modules also include a final class project run completely within Jupyter Notebooks.
Modules allow students from different fields of studies to get familiarized with the foundations of data analysis.
You can learn more about the modules the DSEP Team has created over the years on the Modules webpage
We have also created a webpage to interact with some of our featured connectors on the Modules Showcase Page.
Creating Your Own Module or Connector¶
The Data Science Education Program has created a separate Creating a Module/Connector Curriculum Guide on how Berkeley professors can create modules/connectors based on Data 8. However, professors from other universities/colleges may find it useful to read through the guide to brainstorm ideas on how to bring Data 8 concepts to specific disciplines, and the infrastructure required to do so.