Zero to Data 8
  • Zero to Data 8
  • LICENSE
  • connectors_modules
  • The datascience Package
  • The Data 8 Pedagogy Guide
  • The Data 8 Textbook
  • Links
  • authoring
    • Authoring Notebooks: Start to Finish
    • Authoring Notebooks
    • Minor Changes to existing Otterized Notebooks
  • cc-adoption
    • Community College(and smaller institutions) Adoption
  • grading
    • Grading with GradeScope
    • Grading Otterized Notebooks
    • Grading Locally
    • Otter Service Standalone
  • jupyter
    • Distributing Notebooks
    • Jupyter Notebook Assignments
    • Jupyter Notebook Assignments
    • Creating Data 8 Assignments
  • labs
    • Worksheets and Discussions
    • Lab Sections
    • Tutor Sessions and Office Hours
  • notebooks-platforms
    • Data 8 Notebooks in Various Forms
  • staff
    • Data 8 Course Staff Structure
    • Roles and Responsibilities
  • syllabus
    • Distributing Notebooks
    • Inspiration
    • Syllabus & Lectures
    • Slides & Lecture Videos
    • Course structure
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The Data 8 Textbook

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Last updated 4 years ago

The Data 8 course supplements every lecture with a corresponding few chapters in it's textbook, . Written by and , every new semester of Data 8 utilizes its interactive capabilities to help cement topics of the class for all students.

The textbook is provided under a CC-BY-ND-NC clause - see [](types-of-content) for more information.

The Book's Software

Inferential Thinking is built upon several software libraries which are actively maintained. The main library used to build the book is called , which is also the same software used to create this Zero-to-Data-8 guide! The language used to teach the course is Python, and is supplemented using a library called datascience, which is a library authored by , David Culler, Alvin Wan, and Sam Lau. The library's source code can be found at the attached link .

Inferential Thinking
Ani Adhikari
John Denero
Jupyter Book
John Denero
here