Training & Tutorials
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Explore the various resources listed on this page for foundational training in data science-driven research.
Back to topNIH Cloud Lab
NIH Cloud Lab removes barriers to cloud adoption by providing no-cost, customized, and scientifically relevant training, making it easier for researchers to learn about and explore the cloud with confidence.
Back to topNational Institute of General Medical Sciences (NIGMS) Sandbox
NIGMS Sandbox repository aims to teach students, researchers, and clinicians, among others, how to utilize the power of cloud technology for the benefit of life sciences applications and research.
- There are 12 cloud learning modules that represent a unique use case or scientific workflow.
- Types of data used across the modules include, but are not limited to, genomics, methylomics, transcriptomics, proteomics, and medical imaging data, in formats such as FASTA/FASTQ, SAM, BAM, CSV, PNG, and DICOM.
- Learning modules range in areas from introductory material to single-omics approaches, multi-omics techniques, single-cell analysis, metagenomics, and artificial intelligence and machine learning (AI/ML) imaging applications.
Science Collaborative for Health disparities and Artificial intelligence bias Reduction (ScHARe) Tutorials
ScHARe Tutorials are powered by the Terra research collaboration platform. Instructional notebooks on the ScHARe Terra Workspace provide step-by-step instructions on:
- How to properly configure your Terra account and cloud environment.
- How to access, plot, and save data from datasets hosted by ScHARe, available on ScHARe through the Google Cloud Public Datasets Program, or stored locally on your computer.
- How to use Jupyter Notebooks to run analyses and combine data across available datasets.
- How to share analyses and results with your collaborators.
- After registering for ScHARe, you can access these instructional notebooks through the Analyses tab in the ScHARe Terra Workspace.
Terra Notebooks Playground
Terra Notebooks Playground is a workspace for trying out Terra functionality as it evolves.
Back to topNIH GitHub Resource Center
NIH GitHub Resource Center contains the following tutorials:
- GitHub Docs is a searchable library of step-by-step self-help articles on tasks from basic to advanced.
- Microsoft Learn for GitHub is a catalog of self-paced modules organized into collections and learning paths to help you progress.
- The GitHub Training Manual is a project-based GitHub 101 course that’s designed for total beginners.
- GitHub Skills is a collection of GitHub repositories that offer short, project-based trainings for you to take while inside GitHub.
Imaging Data Analysis Tutorials from the Medical Imaging & Data Resource Center (MIDRC)
Imaging data analysis tutorials from MIDRC are Jupyter notebook tutorials to read in, manipulate and analyze MIDRC data.
Back to topAIM-AHEAD Programs
The National Institutes of Health’s Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) program has established mutually beneficial, coordinated, and trusted partnerships. These partnerships aim to enhance the participation and representation of researchers and communities currently underrepresented in the development of AI/ML models. The program also seeks to improve the capabilities of this emerging technology, beginning with electronic health records (EHR) and extending to other diverse data to address health disparities and inequities.
AIM-AHEAD Programs include:
- Leadership Fellowship
- Research Fellowship
- Professional Development Program
- AIM-AHEAD Training Practicum (PRIME)
- AIM-AHEAD All of Us Training Program
- AIM-AHEAD and the National Center for Advancing Translational Sciences Training Program
Additional Resources
- NIH Data Science Training Resources
- National Library of Medicine’s Data Science and Informatics (DSI) Scholars Program
See additional resources that may be of interest but are not endorsed or supported by NIH (links are external):
Back to topDecember 2024