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    Education: Training in genomics workflows for computational novices
    Submitted by Erin Becker; posted on Monday, June 03, 2019

    Wish your lab team could level-up their computational skills for working with sequencing data? Data Carpentry (https://datacarpentry.org) provides training to get your team away from messy spreadsheets to writing their own custom Bash scripts and computing in the cloud. Our volunteer Instructors are graduate students, postdocs, and other active genomics research professionals who are trained in real-time instruction to customise their teaching to your audience. Instructors build on their audience's existing knowledge to enable them to quickly apply skills learned to their own research.

    We deliver a consistent, high-quality learning experience. Our lessons have been taught over 1000 times and are continuously improved and updated by our community. We create a friendly environment for learning to empower researchers – 91% of our learners recommend our workshops, and 78% stably integrate the tools we teach into their own work.

    We provide comprehensive event handling, from registration through assessment. As a community of volunteers, our workshop fee is highly competitive, covering our administrative costs and core operations. With over 1600 Instructors in 50 countries, we work to find local instructors to minimise costs to you.

    Learn more (https://zenodo.org/record/3237821/files/Genomics-flyer-A4.pdf?download=1) (PDF) or book a workshop (http://carpentries.org/request-workshop) today.

    Data Carpentry is a lesson program within The Carpentries (http://carpentries.org) – a fiscally sponsored project of Community Initiatives (https://communityin.org), a registered 501(c)3 non-profit. The Carpentries builds global capacity in essential data and computational skills for conducting efficient, open, and reproducible research. We train and foster an active, inclusive, diverse community of learners and instructors that promotes and models the importance of software and data in research. We collaboratively develop openly-available lessons and deliver these lessons using evidence-based teaching practices. We focus on people conducting and supporting research.

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