UC Berkeley Data Science Modules

Data Science for the Social Sciences¶

It is no secret in industry that data has impacted every facet of human life. In the modern age, researchers are now adopting new techniques to leverage data science and statistics to their unique disciplines. At the Data Science Education Program (DSEP) at UC Berkeley, we believe in providing opportunities to students to be exposed to this paradigm shift.

These curriculums are developed in conjunction with the professors of various departments, and by the volunteering work of the modules student developers. Feel free to take a look at the wealth of curriculum resources on the left of the screen.

Data Science at Berkeley¶

In the Fall of 2018, the UC Berkeley Division of Data Sciences and Information released the official Bachelor of Arts (B.A.) in Data Science major. Even before then, many years of planning went into increasing the exposure of the data sciences to the ungraduate community of Cal. From it’s inception in 2017, Data 8: The Foundations of Data Science has become the fastest growing class in Berkeley’s history. From that rising popularity came the construction of many other data science classes, such as the supplemental 2-unit Connector Courses, as well as the liberal arts-focused Modules program.

Data Science Education Programs (DSEP)¶

The DSEP team at UC Berkeley is an autonomous working arm of the Division of Data Sciences and Information. The team is made up of a variety of professors, graduate and undergraduate students motivated to improve the way data science is being taught across all college and K-12 education systems. Our mission is to democratize data science pedagogy by integrating statistical analysis lectures and curriculum materials into the social sciences.

Jupyter Book¶

This website was created using Jupyter Book. Jupyter Book lets you build an online book using a collection of Jupyter Notebooks and Markdown files. Its output is similar to the excellent Bookdown tool, and adds extra functionality for people running a Jupyter stack.

Here are a few features of Jupyter Books

• All course content is written in markdown and Jupyter Notebooks, stored in notebooks/
• The Jupyter Book repo comes packaged with helper scripts to convert these into Jekyll pages (in scripts/) that can be hosted for free on GitHub
• Pages can have Binder or JupyterHub links automatically added for interactivity.
• The website itself is based on Jekyll, and is highly extensible and can be freely-hosted on GitHub.
• There are lots of nifty HTML features under-the-hood, such as Turbolinks fast-navigation and click-to-copy in code cells.

License¶

The contents of this book are licensed for free consumption under the following license: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)