Training Resources for Data Science
Fred Hutch DaSL Courses and Guides
| Course Name | Description | Link(s) |
|---|---|---|
| Cluster 101 | Intro to using the Fred Hutch HPC cluster for new or experienced users. Provides a certification option. | With Certification or Without Certification |
| WDL 101 | Intro to using Cromwell to run WDL workflows at the Fred Hutch | Course link |
| Code Review | Leading a lab with novice or experienced code writers and users? Either way, our Code Review guidance materials include helpful suggestions for various types of lab members, expertise and group dynamics. | Course Link |
| NIH Data Sharing | We have created and are actively developing a guide that walks you through the process of complying with the new 2023 NIH Data Sharing Policy. | Guide Link |
Cluster 101
We collaborated with SciComp and created a course called Cluster 101, to introduce new and experienced high performance computing users to the Fred Hutch cluster. This course can be taken anytime, anywhere, for free (don’t worry just set the Leanpub cost to zero) and it’ll help you check to make sure your account is set up to use the cluster and either help you check to make sure you understand the basics of how to use a cluster, or help you get up to speed. It can even give you a certification for reporting between staff and lab leaders if need be.
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If you need/want to get a certification, please take the course through Leanpub at this link.
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If you do not need the certification or want to bookmark the course for future reference, you can find the material at this link.
If you take this course and want to give us feedback or would like to learn more about it, you can share your thoughts in Slack in the #ask-dasl channel) or you can file an issue on the course’s GitHub repository.
WDL 101
Our next emerging guide is WDL 101: Using Cromwell at the Fred Hutch which will help users leverage our preconfigured software to allow you to run and manage all of your computing jobs, as well as run workflows written in WDL (a widely used open specification for workflow description), even if they use Docker containers! This is an excellent tool for researchers who do not use large scale computing resources often or who would want a method to simply upload a file and use a website to submit jobs to the cluster. Also, for researchers who do leverage amount of cluster resources, this approach can help you make your computing more efficient, help you to scale up your pleasantly parallel work and shift to using containers and structuring tasks appropriately to facilitate moving to the cloud when needed. This guide is under active development as of Nov 2022.
If you take this guide and want to give us feedback or would like to learn more about it, you can share your thoughts in Slack in the #ask-dasl channel) or you can file an issue on the guide’s GitHub repository.
Code Review
Leading a lab with novice or experienced code writers and users? Either way, see our Code Review materials that include helpful suggestions for various types of lab members, expertise and group dynamics.
If you take this course and want to give us feedback or would like to learn more about it, you can share your thoughts in Slack in the #ask-dasl channel) or you can file an issue on the course’s GitHub repository.
NIH Data Sharing
We have created and are actively developing a guide you can find here that walks you through the process of complying with the new 2023 NIH Data Sharing Policy. We have also created the DMS Helper App to make filling in and downloading your data sharing plan easier.
If you take this course and want to give us feedback or would like to learn more about it, you can share your thoughts in Slack in the #ask-dasl channel) or you can fill out our Google Feedback Form.
Full List of Training Resources
FH DaSL staff have developed many training resources as part of collaborations and efforts. Various resources spanning a wide range of data science and tool-specific topics that we have previously developed are available from the sources listed below.
- For the full list of DaSL supported resources go here.
- For a longer list of recommended resources (not just ones supported by us, go here).
(in alphabetical order)
AnVIL
AnVIL is a computing platform that enables researchers to analyze controlled access data sets in a cloud computing environment. It has loads of training materials to support those using it!
Code Review Guidance for Research Labs
Leading a lab with novice or experienced code writers and users? Either way, see our Code Review materials that include helpful suggestions for various types of lab members, expertise and group dynamics.
DataTrail
The DataTrail courses are free and designed to help those with less familiarity with computers and technology become savvy data scientists. It includes the technological data science fundamentals but also information on how to network and other accompanying and necessary skills for jobs in data science.
ITCR Training Network
The ITCR Training Network is an effort to catalyze cancer informatics research through training opportunities. It has online courses that are available for free and/or for certification, but also hosts synchronous training events and workshops related to data science in cancer research. Links to all the current ITCR courses can be found here
Johns Hopkins Data Science Courses
There are a lot of helpful resources for data science that we made as a part of Johns Hopkins. These courses cover various applications and tools of data science, mostly focused on using R and the Tidyverse.
Open Case studies
The Open Case Studies project can be used by educators and learners alike to help people learn how apply data science to real-life data.