Fred Hutch Data Science Lab
- 62 followers
- United States of America
- https://hutchdatascience.org/
- channel/UCVYkwYANVSJtHRX5x6WD8gQ
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Choosing_Genomics_Tools
Choosing_Genomics_Tools PublicBased on their genomic data types and goals, this course will help learners find educational resources and tools to help them process and interpret data.
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code_review
code_review PublicA repository with tips about code review and implementing it in a lab
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AI_for_Efficient_Programming
AI_for_Efficient_Programming PublicThis course on AI for software development explores the use of AI large language models (ChatGPT, Bard, etc) and their potential benefits and challenges. Hands-on activities show the ways in which …
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Containers_for_Scientists
Containers_for_Scientists PublicThis course covers how to use containers for scientific software development. Scientific software benefits from the concepts of continuous integration (CI) and continuous deployment (CD). Container…
Repositories
- Data_on_AnVIL Public
This is a guide to all the ways to access, upload, and use data on NHGRI's AnVIL platform.
- Intro_to_Python Public
The course covers fundamentals of Python, a high-level programming language, and use it to wrangle data for analysis and visualization.
- Intro_to_R Public
The course covers fundamentals of R, a high-level programming language, and use it to wrangle data for analysis and visualization. The programming skills you will learn are transferable to learn more about R independently and other high-level languages such as Python.
- AnVIL_Collection Public
📚 An auto-generating collection of all materials related to the AnVIL and GDSCN projects
- AnVIL_Outreach_Metrics Public
Metricminer Dashboard for the AnVIL Outreach Team and associated metrics
- NIH_Data_Sharing Public
Learn about the new NIH data sharing policy, places where you might want to share your particular kind of data, and how to deal with possible challenges associated with the policy.
- Containers_for_Scientists Public
This course covers how to use containers for scientific software development. Scientific software benefits from the concepts of continuous integration (CI) and continuous deployment (CD). Containers play a critical role in CI/CD by providing a consistent, portable, and isolated environment for building, testing, and deploying software.
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