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Overview of SCINet Training Opportunities

One of SCINet’s main objectives is training scientists in computational methods to empower agricultural research. We are doing this in several ways. We offer online and in person trainings, support topic-specific working groups, and provide help, training, and tutorials for scientists.

Get Started with SCINet Learning Pathway

With the expansive list of free training available online, finding the right training to meet your learning needs can be daunting. Take the first steps in getting started with your introductory learning path to help you get started with SCINet. Learn about SCINet, how to sign up for an account, and what is possible when supported by SCINet infrastructure. Then dive in with hands-on tutorials available across multiple searchable platforms to find the information you need for just-in-time learning.

Get Started Dive Deeper Find Your Community
Getting Started Dive Deeper Find Your Community
Watch these videos to learn how to get started with SCINet Explore these training resources to find specific content to meet your research needs Find others in your community to work with, get answers, and explore ideas with
Intro to SCINet Coursera Working Group
SCINet Onboarding Carpentries: UNIX, GIT, Python, R, OpenRefine, SQL SCINet Forum
Atlas Overview AgLearn: LinkedIn Learn, Precipio SCINet Corner
Intro to Command Line Geospatial Workbook  
  Bioinformatics Workbook  


Additional Training Resources


Resource Links Description
Upcoming Trainings Browse all scheduled trainings
Free Online Trainings Explore the extensive list of free online trainings organized by topic
Intro to UNIX Tutorial on UNIX commands
Long term storage and Juno Learn more about SCINet’s data storage options, suggested workflows for using SCINet storage for your research, and how to efficiently move data between SCINet’s storage systems.
Machine Learning Tutorial Tutorial introducing machine learning methods using Jupyter notebooks and coding excercises
Geospatial Analysis with Python on Ceres Tutorial on efficient data practices, using JupyterHub and Lab on Ceres, using Dask for parallel computing
NEON High Resolution Hyperspectral Data Exercise Tutorial to explore NEON AOP hyperspectral data, calculate/visualize spectral indices, unsupervised ML (clustering)
Quantitative Trait Locus (QTL) Analysis for Breeding Tutorial on how to use QTL-surge and RStudio on Ceres


Useful Links


Useful Links Description
Quick Start Guide Use this step-by-step guide to walk you through getting started with SCInet and answer common trouble shooting questions
Data Management Resources and links to support data management
Ceres User Manual Guide to getting started with Ceres including a technical overview and system configurations.
Atlas HPC User Guide Guide to accessing Atlas including transferring files and quotas.
Iowa State HPC Site Guide on compute clusters, UNIX command line, building containers, and data transfer with Globus.
Ag Data Commons Public, government, scientific research data catalog and repository to share and discover research data funded by the United States Department of Agriculture and meet Federal open access requirements. Through the Ag Data Commons, the USDA National Agricultural Library (NAL) provides services to make USDA funded research data systems and data products Findable, Accessible, Interoperable, and Reusable (FAIR). Critical functions the Ag Data Commons provides include: Scientific metadata creation and curation, Public access to data through a catalog of USDA funded research and public APIs, Data repository for long-term archiving (as required to support DOI service)