February 29, 2020 | Written by: Naguib Attia
Categorized: Education | skills
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The project, named OpenDS4All, was initiated and funded by IBM with the goal of accelerating the creation of data science curricula at academic institutions.
It hosts educational modules that may be used as building blocks for a data science curriculum. Based on Python and open source tools and frameworks, they include slides, documentation, code and links to public data sets.
All the modules, built for professors by professors, combined make up a set of materials to build a Data Science Program on top of required prerequisites, and they are connected through the cycle of data preparation, data exploration, model training, and model selection, model validation and implementation
The starter kit is organized into categories: Foundation, Data Wrangling and Integration, Exploratory Data Analysis, Data and Knowledge Modeling, Scalable Data Processing, Machine Learning, Model Assessment and Ethics. See GitHub page. There is a topology on the 1st page showing how content is organized for the initial phase. As the project grows this topology will be updated accordingly.
Each category contains modules and each module consists of one or more of the following components:
a set of PowerPoint slides (with presenter notes)
a Jupyter notebook
a homework assignment
additional documentation (where applicable)
This is a new/revolutionary approach: these educational materials are published available under the Creative Commons 4.0 and Apache 2.0 licenses. It is now possible for any university to take these modules and use them at no cost to develop their own Data science programs. Additionally, community members have the opportunity to contribute to continuously enhance/update the modules and therefore this curriculum kit will remain updated and relevant to the latest and greatest data science techniques and technology updates.
Access the OpenDS4All starter kit via the IBM Academic Initiative, Data Science Courseware tile.