The open data science for all resources contains the building blocks for a data science curriculum organized by category.
The curricular materials are divided thematically, much as chapters in a book. The content & organization file describes the basic directory structure.
Generally speaking, we recommend a "flow" of topics that goes from the core foundational overview ("what is data science"?), to data representation and wrangling, to machine learning models, to model tuning and assessment. Topics such as data visualization and data ethics are generally important but can be ordered in a variety of ways.
Please see the instructor's guide for suggested configurations of course materials. We also recommend you consult the getting started guide for Jupyter Notebook for information on how to set up Jupyter Notebook for your students.