The OpenDS4All content is organized in a hierarchical structure containing the following categories:
opends4all-resources - contains the opends4all curriculum building blocks organized by category
- opends4all-overview - provides an overview of the topics in the OpenDS4All curriculum, including big data, data science, and data engineering.
- opends4all-instructor-resources - includes materials for helping instructors plan curricula, set up a computing environment, and so on.
- opends4all-foundation - contains modules on the foundation of data science, including mathematics, statistics and computer science
- opends4all-data-wrangling-and-integration - contains modules on data access, data preparation, data transformation and data integration
- opends4all-exploratory-data-analysis - contains modules on data summarization and visualization
- opends4all-data-and-knowledge-modeling - contains modules on data and knowledge modeling (models for storage of data as well as computer interpretable models of knowledge)
- opends4all-scalable-data-processing - contains modules on parallel and distributed processing as well as big data
- opends4all-machine-learning - contains modules on supervised, unsupervised, semi-supervised, reinforcement and deep learning
- opends4all-model-assessment - contains modules on model assessment using graphical and other means
- opends4all-ethics - contains modules on ethical consideration in data science
Each category contains one or more modules, identified by a descriptive name, keywords, skill level and file extension. See NAMING-CONVENTIONS.md for more details.
License: CC BY 4.0, Copyright Contributors to the ODPi OpenDS4All project.