Northeast Student Data Corps – Educator Central


Northeast Student Data Corps – Educator Central

Welcome Educators!

Data science is more important than ever in today’s digital world and has applications in all disciplines. The resources below can help you whether you are building a new data science program at your school, running a lab and looking for datasets, or just interested in how you can incorporate data science topics in your classroom.


Curriculum Materials

Build a data science curriculum that works for your students using these frameworks from different universities and organizations.

Data 8: Foundations of Data Science

This course from UC Berkeley covers statistics, data visualization, machine learning, and basic programming in Python.

DSC 101: Introduction to Data Science

Created and taught by NSDC Founding Committee member Ajay Anand, this introductory course was adapted from the Data 8 course. Assignments and corresponding code workbooks can be accessed at bit.ly/data8assets.

Open P-TECH

This curriculum from IBM covers topics ranging from cybersecurity to artificial intelligence. Register now and earn digital badges to demonstrate your accomplishments.

OpenDS4All

Explore lecture slides, instructor notes, Jupyter notebooks with hands-on examples, and homework assignments on topics including data wrangling and machine learning.

International Data Science in Schools Project

This international collaborative project provides a pre-calculus course for high school students and a course for educators on teaching data science.

The Missing Semester

This MIT course covers the skills often skipped in computer science courses. Help your students master the command line, learn data wrangling, and use a powerful text editor and version control system.

Binghamton University MS in Data Analytics

This program is a collaboration across STEM, business, and engineering departments. Students learn how to analyze data and work on projects tackling real-world problems.

CUNY City Tech BS in Data Science

This program synthesizes applied mathematics, high-performance computing, and data management and analysis for a well-rounded data science education.

Data: Past, Present, Future

This Columbia course integrates the teaching of algorithms and data manipulation with the political whirlwinds and ethical controversies from which those techniques emerged.

Global Columbia Collaboratory

This program enables students to learn about global challenges and collaborate on projects to address them, which can be data and technology-driven.

Data Science Ethics

Visit NSDC – Learner Central for resources on data science ethics issues including privacy, informed consent, and bias.

Datasets

Use these datasets for research or to help students practice data analysis.

Consortium of Universities for the Advancement of Hydrologic Science, Inc.

Access thousands of hydrologic, biogeochemical, and geographic datasets from U.S. agencies, university projects, and community initiatives.

NYC Open Data

Published by New York City agencies and other partners, NYC Open Data provides datasets on city government, environment, health, and more.

UCI Machine Learning Repository

Explore the University of California, Irvine’s repository of over 550 datasets on diverse topics.

Kaggle

Discover and publish datasets on any topic you're interested in, collaborate with other data scientists, and find competitions to solve data science challenges.

Analyze Boston

Explore datasets on issues of finance, city services, public safety, the environment, and more from Boston's open data hub.

Check out the NSDC Learner Central for more resources for students.

Join other data science educators on our Slack community!