The workshops are open to all PhD students, Postdoc and researchers within the Faculty of Mathematics and Natural Sciences. Find more information about the workshops below.
Workshop 1: Version control
Workshop Description
The workshop starts with a basic theoretical understanding of version control and its main components. Shortly after, participants start with a demo project going through the basic commands and establishing a practical understanding of git/GitHub. Next, participants develop a collaborative demo project in a single-branch context and they proceed to repeat the same in a multi-branch context. In the last steps, some more advanced features of Git/Github will be explored.
List of the learning outcomes
-
Basic terminology around version control using git and github
- Establishing git-github connection
- Version control operation using command line
- Version control operations using Graphical user interfaces (RStudio and VSCode)
- Single- and multi-branch version control developments
- Resolving merge conflict
- Keeping track of versions and moving back to history
Prerequisites
- Familiarity with programming languages
- Basic familiarity with command line operation and code editing platforms
Target audience
PhD student, postdocs and researchers who are involved in data analysis and programming.
Duration of the workshop
3 x ½ days
Pre-register
You be notified when the next workshop is scheduled.
Workshop 2: Project management for PhD students
An introduction to tools, techniques and strategies for a more effective management of a PhD project.
Workshop Description
The workshop is designed to give PhD students a broad and comprehensive perspective into strategies, tools, techniques and a set of collective experiences related to management of a PhD project. The content covers areas such as knowledge management, progress management, analysis and software management, reporting and dissemination as well as human interaction aspects of the project management. We will discuss “dos and don’ts” and a set of best practices around the mentioned areas, and also include time for discussion and exchange of personal experiences.
List of the learning outcomes
- Knowledge management:
- acquiring, organizing, preserving knowledge
- Knowledge and reference management tools
- Progress management:
- Quick note-taking, Progress logs, Gantt chart and thinking ahead,
- Project management tools
- Analysis and software management:
- Inline code documentation, Function and module based code development,
- Version control, Dependency and environment management,
- Making R and python packages
- Reporting and dissemination:
- R markdown, Jupyter notebook, Quarto
- Shiny
- Github
- Zenodo
- Teamwork and coordination:
- Progress update to collaborators
- Self-assessment of the progress
- Keeping up morale
Prerequisites
Master’s degree
Target audience
The course is ideally designed for first year PhD students but those beyond the first year can benefit from the course as well.
Duration of the workshop
3 x ½ days
Pre-register
You will be notified with the next workshop is scheduled.
Workshop 3: Building packages in R
Hands-on workshop on building R package.
Workshop Description
The workshop starts with an introduction to the role of R packages in programming in R. Afterwards, participants build a demo package around some exemplary functions. Next, they will go through the developmental stages of creating a R package. In addition, the participants get to install and share packages with each other and learn the collaborative aspects of building a R package.
List of the learning outcomes
- Basic concepts and technical terms around R packages
- How to document scripts for R packages
- Detail developmental stages of building a R package
- Dissemination and sharing of R packages
Prerequisites
- Familiarity with programming in R
Target audience
PhD student, postdocs and researchers who are involved in data analysis and programming.
Duration of the workshop
3 x ½ days
Pre-register
You will be notified with the next workshop is scheduled.
Workshop 4: Building packages in Python
Hands-on workshop on building Python package.
Workshop Description
The workshop starts with an overview of general installation and usage of packages in Python. Afterwards, participants build a demo package and go through the developmental stages of creating a python package. Furthermore, they will engage in installing and exchanging packages with other attendees, exploring the cooperative dimension of Python package development.
List of the learning outcomes
- Basic concepts and technical terms around Python packages
- How to document scripts for Python packages
- Detail developmental stages of building a Python package
- Dissemination and sharing of Python packages
Prerequisites:
- Familiarity with programming in Python
Target audience:
PhD student, postdocs and researchers who are involved in data analysis and programming.
Duration of the workshop
3 x ½ days
Pre-register
You will be notified when the next workshop is scheduled.
Workshop 5: HPC Visualization using ParaView
Time and place:
Friday 21.06.2024 09:00-12:00, at Ole-Johan Dahls hus: Seminarrom Python
Workshop Description
The objective of this workshop is to raise awareness among users about the possibilities and potential of ParaView in scientific visualization, particularly when leveraging high-performance computing (HPC) infrastructure like Norwegian AI Cloud (NAIC).
List of the learning outcomes
- Introduction to ParaView
- Python Scripting for Automation
- Extending ParaView
- ParaView under NAIC
- Advanced Topics
Prerequisites:
Knowledge in Python scripting.
Please come with a laptop (with ParaView installed), so that you can try out some of the examples. Visit this link to install ParaView.
Exercise files, sample datasets, and presentation files will be made available on the day of workshop.
Target audience:
All interested
Duration of the workshop
½ day