Wed - Thu 22 Jul 2026 - 23 Jul 2026Past

Advanced Git

Workshop Bonn (Bonn University)
Workshop Git GitLab Carpentries By DKZ.2R
Registration Closed

A workshop offered in collaboration with the Graduate center of Bonn University.

In this workshop, we will look at the steps beyond “git add” and “git commit” and look at some of the less frequently used (but still important!) git commands to help you resolve common issues that arise in git controlled projects.

We will cover the following Topics (selection):

  • Branching and Remotes (branch, switch, remote)
  • Undoing Changes (revert, reset)
  • Merging & Resolving Merge Conflicts
  • Tagging (tag)
  • Branching Models and Workflows
  • Cherry Picking (cherry-pick)
  • Rebasing (rebase, interactive rebase)

Workshop material is available online and will be presented by official Carpentries instructors, who will guide you through the concepts with the help of hands-on exercises and personalized support. The course is designed for those with a basic familiarity with git and the git workflow and is open to participants from all domains.

To participate in the course please bring your own laptop.

If you are interested in taking part in the workshop, you can sign up here.

  • Title: Advanced Git
  • When: Wednesday, July 22nd & Thursday, July 23rd(09:00am-5pm)
  • Where: Bonn (University Bonn)
  • Format: This workshop in In-Person and no remote or online attendance options are currently planned.
Tags:

Related Posts

Intro to Programming with Python

As part of our “Trainings” work package, the DKZ.2R creates, curates and presents a variety of free trainings, seminars and courses. Our next offering will be a two-day Python Intro course in collaboration with hpc.nrw. The Lecture part of the workshop will be streamed live from Bonn to different locations where participants are supported by on-site instructors in working on the exercises and in the case of questions. The DKZ.2R will support participants on-site in Aachen for the two-day event.

Read More
Carpentries Workshop - Introduction to Python

Carpentries Workshop - Introduction to Python

Empowering Researchers with Foundational Computing Skills: Join the Upcoming Carpentries Workshop

In today’s fast-paced research environment, the ability to harness computational tools effectively can make a world of difference. Whether you’re managing data or automating tasks, having the right skills can significantly streamline your work. That’s where The Carpentries come in — a global initiative comprising the Software Carpentry, Data Carpentry, and Library Carpentry communities. These communities are dedicated to equipping researchers with essential computational and data science skills, helping them to work smarter, not harder.

Read More
How To: Good Scientific Practice

How To: Good Scientific Practice

“Scientific integrity forms the basis for trustworthy research”, so it says in the Guidelines for Safeguarding Good Research Practice of the DFG, the German Research Foundation. As a major funder of research in Germany the DFG, as well as many other funders of research in Germany and the European Union, requires researchers to follow a certain set of rules conducting their research. These rules are called “good scientific practice” and have to be followed by researchers to be viable for funding. According to the guidelines researchers are required to “document all information relevant to the production of a research result as clearly as is required by and is appropriate for the relevant subject area to allow the result to be reviewed and assessed”. But good scientific practice is not done by documenting your research. It also includes i.a. protecting the personality rights of your subjects and handling research data in an appropriate manner by e.g. “back(-ing) up research data and results made publicly available, as well as the central materials on which they are based and the research software used, by adequate means according to the standards of the relevant subject area, and retain them for an appropriate period of time.” This is where Research Data Management (RDM) comes in. Of course RDM is much more than just creating a backup of your data on a USB-Stick and handing it over to anyone asking for it. “Good scientific practice” in RDM follows the FAIR principles:

Read More