Data Repository

This data repository is a project designed to serve as a comprehensive hub for learning resources in the field of data science. The primary goal is to create a centralized platform that aggregates and organizes a vast array of high-quality materials, including tutorials, courses, articles, and tools, making them easily accessible to learners at all levels.

By curating a diverse range of resources, we aim to cater to the needs of:

  • Beginners seeking foundational knowledge
  • Intermediate learners looking to deepen their skills
  • Experienced professionals staying abreast of the latest developments

This repository fosters inclusivity, allowing individuals from various backgrounds and expertise levels to engage with the dynamic world of data science. The benefits extend beyond individual learners; educators, industry professionals, and researchers can also leverage this repository as a valuable reference and teaching tool.

Ultimately, this initiative aims to democratize access to knowledge, empowering a global community to thrive in the ever-evolving landscape of data science.

Resources on campus

The University of Notre Dame has several centers and institutes that provide resources for learning data science.

Hesburgh Library resources
Navari Family Center for Digital Scholarship
Office of Information Technologies (OIT)
ND Learning
  • View the hub’s collection of resources here

Secondary Data


Common Terminology

Data Repositories

Data Repositories

Data Repositories

General Computing Links


Disclaimer: This repository is a curated collection of links to various external learning resources related to data science. Please note that the inclusion of these links does not imply ownership or endorsement by Lucy Family Institute. The provided links direct users to third-party websites, and their content, accuracy, and availability are subject to change without prior notice. Lucy Family Institute bears no responsibility for the content, functionality, or any potential updates or modifications made to the linked materials. Users are encouraged to review the terms of use, privacy policies, and licensing agreements of the respective websites before accessing or utilizing the content provided through these links. The repository is intended for informational purposes only, aiming to facilitate access to diverse resources related to data science. Users should exercise discretion, verify the authenticity, and validate the relevance of the information presented in these external resources before relying on it.