data-8/zero-to-data-8

Name: zero-to-data-8

Owner: Data Science 8

Description: null

Created: 2018-01-24 16:07:59.0

Updated: 2018-05-14 16:25:01.0

Pushed: 2018-05-14 16:25:00.0

Homepage: https://berkeleydsep.gitbook.io/zero-to-data-8/

Size: 84

Language: Python

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README

An Educator's Guide to Data 8

Data 8 is a “Foundations in Data Science” course taught for first year students at UC Berkeley. It combines principles/skills in statistics, programming, inference, modeling, hypothesis testing, visualization, and exploration. In short, it provides a foundation in the many fields encompassed by “data science”, and gives students a practical introduction to the field.

This online resource serves as a “snapshot” of the Data 8 stack, and a guide providing a path forward for others that wish to imitate the Data 8 model. It represents all of the components that go into making Data 8 what it is. Including both pedagogical approach, concepts / topics covered, and technical pieces used in the class.

See the chapters to the left to navigate this book. Below is a general structure of the material.

The Data 8 project has several components, all of which are freely-available and open-source.

Deploying your own Data 8 course from scratch

The first section of this guide is a step-by-step guide that teaches you how to deploy your own version of Data 8. It explains how to create a JupyterHub running in the cloud that students can access, how to connect this JupyterHub with the coding environment that Data 8 students use, and how to incorporate course materials into your class. Check it out here:

Technical and pedagogical decisions for Data 8

These sections cove the high-level reasoning behind the Data 8 course, including an overview of the technical and pedagogical pieces that make up the course. It should be treated as a reference for running your own Data 8 course, or for taking a similar technical approach to teaching data science.

Other Data 8 information

All Data 8 materials are freely available online. The course material in full can be accessed at the following online resources:

To explore the guide, select a section to the left!


This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.