Zero to Data 8
  • Zero to Data 8
  • LICENSE
  • connectors_modules
  • The datascience Package
  • The Data 8 Pedagogy Guide
  • The Data 8 Textbook
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  • authoring
    • Authoring Notebooks: Start to Finish
    • Authoring Notebooks
    • Minor Changes to existing Otterized Notebooks
  • cc-adoption
    • Community College(and smaller institutions) Adoption
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    • Grading with GradeScope
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  • jupyter
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    • Jupyter Notebook Assignments
    • Creating Data 8 Assignments
  • labs
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    • Data 8 Notebooks in Various Forms
  • staff
    • Data 8 Course Staff Structure
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  • syllabus
    • Distributing Notebooks
    • Inspiration
    • Syllabus & Lectures
    • Slides & Lecture Videos
    • Course structure
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  1. syllabus

Syllabus & Lectures

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Last updated 4 years ago

Teaching Data Science requires a shift in the way we traditionally teach each of the individual concepts in the course. What were once several introductory courses in statistics, computer science, writing, and ethics (among others) are now combined into a single introductory course.

In Data 8, touching on these topics in a single course is a feature, not a bug. For example, by teaching programming with the fundamentals of statistics, students gain an appreciation for the close interplay between these two fields and learn a valuable set of skills at the same time. Through this course, students are able to learn how to interpret and ask questions about their data with the support of inferential and computational tools.

This section covers many of the pedagogical decisions that were made in Data 8. It should be seen as a reference and background for the , which is freely-available online.

Data 8 textbook