General Resources

Explanation of what comprises Data Science and Data Scientists. Tutorial on how these tools can be applied in the workplace.

This is a full course from CMU covering algorithms. It includes lecture notes by topic and date as well as homework, quizzes and exams with solutions.

The materials on this page are community developed curricula for teaching Earth Engine in higher education.

Cutting-edge news on data analytics and data science pieces.

A cache of informative articles about data science, categorized into data science, machine learning, programming, visualization, and AI.

Weekly curated news picks covering machine learning, data visualization, analytics, and strategy.

An online platform on business analytics, big data, data mining, and data science. The platform covers analytics and data mining, including news, software, jobs, meetings, courses, data, education, and webinars.

The internet’s most useful data science articles.

A highly curated selection of the best in Machine Learning, AI, Data Science, and Data Engineering every week. Featuring a very minimalist interface.

Free newsletter including news, articles, and careers relating to data science. Includes videos and tutorials as well.

Weekly insight from industry insiders on data science. Provides a great snapshot of tech and big data. O’Reilly has also come out with ebooks and host conferences, along with other learning tools.

Provides a variety of workshops regarding research computing. Structure is generally a brief lecture followed by a hands-on session. Held in the Data Visualization Lab in the Kathleen A. Zar Room in the Crerar Library.

Explore a variety of workshops that cover a wide range of topics from finding and managing data to spatial data analysis. Learn how to perform a specific workflow using a specific tool that is commonly used in the earth data science field.

Notes on various EDI workshops ranging from data publication training to hackathons.

Data recipes are tutorials to help users learn how to discover, access, subset, visualize and use our data, information, tools and services. These recipes cover many different data products across the Earth science disciplines and different processing languages/software.

Tutorials include step-by-step instructions to help users learn how to discover, access, subset, visualize and use Earth science data, information, tools and services. These tutorials cover many different data products across the Earth science disciplines and different data discovery and data access tools, including programming languages and related software. Webinars span the Earth science disciplines and are designed to help users learn about NASA EOSDIS data, services and tools and show users how to work with these data resources.

Code and trained models on GitHub.

The September bootcamps introduce relevant computational and statistical tools. They are intended to give new and continuing PhD students a jumpstart into the practical skills needed for conducting research. The 1- and 2-week courses are hosted and organized by our current NRT fellows. Lessons are applicable to a wide range of fields, but examples will be drawn from environmental sciences.

The Data Management Training Clearinghouseis a registry for online learning resources focusing on research data management.

Data pathfinders provide direct links to commonly-used datasets across NASA’s Earth science data collections. These pathfinders supplement the search capability by providing datasets through commonly used tools; these tools provide different ways of visualizing the data, options for subsetting the data, and options for saving the data in different file formats.

The (EDI) data portal contains environmental and ecological data packages contributed by a number of participating organizations.

contains ecological data packages contributed by past and present LTER sites.

is a page that contains a collection of various data sets of climate change and of environmental trends that it sorts by region or relevancy to what is being searched. The goal is to give people the opportunity to access quality and accurate data sets to do relevant research.

A planetary-scale platform for Earth Science data and analysis. Earth Engine’s public data archive includes more than forty years of historical imagery and scientific datasets, updated and expanded daily.

Collection of tools for creating visualizations for different types of data. Many of these tools provide access to near real-time imagery from some of NASA’s Earth observation missions, allowing for near-real time response to natural and man-made events.

AI for Earth hosts key geospatial and conservation datasets on Azure. Anyone can use these data sets to operate on global-scale environmental data.

Published research for various AI for Earth projects.

Website that focuses on recording and collecting Data (particularly climate/weather and topography) over Europe and the rest of the planet. I would classify it as a platform website and it focuses more on having data sets than programming languages.

Explore publications and contributions made by the ESIP community as a whole. Includes data publication guidelines, software guidelines, training, etc.

AI for Earth APIs allow application developers to accelerate their conservation applications with machine learning. Note: some API’s require requests.

Open-source infrastructure and hands-on development support to go from a machine learning project to a web API running on Azure.

Tools for functions such as searching and subsetting data. The tools are categorized by type that indicate the primary function, including:
Search and Order
Data Handling
Subsetting and Filtering
Geolocation, Reprojection, and Mapping
Data Visualization and Analysis

contains a list of APIs.

afree, regularly updated textbook. It is an introduction to programming, teaching you basic concepts of organizing data and the programs that operate over them, ending in the investigation of universally useful algorithms. It is also an introduction to programming languages: a study, from one level up, of the media by which we structure these data and programs.

An international, interdisciplinary journal for the publication of articles on original research data (sets). The journal maintains sections for regular-length articles, brief communications (e.g. on additions to data sets) and commentaries, as well as review articles and special issues.

The purpose of Earth Engine is to: Provide an interactive platform for geospatial algorithm development at scale, enable high-impact, data-driven science, make substantive progress on global challenges that involve large geospatial datasets. Guides cover topics ranging from machine learning to image collection and algorithms.

A detailed overview of using Miway2, the high-performing computing system.