# Summer Intern Data Carpentry Workshop  --- Before we start... ## Code of Conduct * We are dedicated to providing a welcoming and supportive environment for all people, regardless of background or identity. --- ## Code of Conduct https://docs.carpentries.org/topic_folders/policies/code-of-conduct.html --- ## Code of Conduct * Go to Instructors or Helpers if you feel the Code of Conduct is being violated. * There is also a big blue "Report a Code of Conduct Incident" on the course website if you feel the Instructors are not handling appropriately. --- ## Introductions ### *Instructors and Helpers* --- ## What is the Carpentries? https://carpentries.org/ The Carpentries is a global volunteer-driven organization dedicated to teaching computational skills to researchers and anyone who works with data. --- ## Carpentries at the Smithsonian https://datascience.si.edu/carpentries The Smithsonian Carpentries Team is made up of Smithsonian staff and fellows from around the institution. --- ## Carpentries way of teaching Code along, rather than lecturing from PowerPoint, or just demonstrating Odds of running into an error are high, but don’t panic – this is a great opportunity to learn --- ## ***We won’t leave you behind*** --- ### How to make sure we don't leave you behind In the real world, we used to use Post-It notes to indicate progress, but for this workshop we'll also use the "yes" / "no" buttons in the Zoom Reactions panel.  --- ## How to ask questions The Instructors will try to build in time between lessons to ask questions, but use the Zoom chat for questions that come up during a lesson.  --- ## Course website https://smithsonian.github.io/2024-07-16-smithsonian/ --- ## Course EtherPad A collaborative document – think of it as a stripped-down version of Google Docs https://pad.carpentries.org/2024-07-16-smithsonian --- ## Your first challenge * Go to the EtherPad * Add your name, unit, and answer the icebreaker question under Attendance for today --- ## What we will be teaching in this workshop Data Carpentry introduces you to the fundamentals of computing and provides you with a platform for further self-directed learning. --- > We will be teaching you a lot of valuable skills on a demo dataset, but you won't be able to add these tools to your *toolbag* until you work through how to apply them to your own data. ---