| Compact Course "Agentic Test-Driven Development"
Dr. Liam Keegan
As agentic coding tools like Claude Code and Codex CLI make generating code faster, validating the correctness of this code becomes more important than ever. In this course you will learn how to apply test-driven development and software testing best practices in the context of agentic software development. By writing tests before the implementation, our test suite not only verifies correctness, but also defines a clear specification of what the code should and should not do. | |
| Compact Course "Continuous Integration with Github Actions"
Dr. Dominic Kempf
Continuous Integration (CI) is one of the cornerstones of agile development processes: Before changes are included into the mainline, a number of tests is run automatically to ensure the quality of the software. In this course, we explain how this process is implemented on GitHub.com (GitHub Actions). After a general introduction, participants will work on setting up Github Actions for their own projects. The SSC is available for follow-up consultation work on the CI workflows developed during this course. | |
| Compact Course "Expert Topics in Version Control with Git"
Dr. Dominic Kempf
Applying version control can be a game changer for a collaborative research software project. However, even in projects that already successfully use Git, there is often room for improvement of the employed Git workflows. This workshop explores some advanced topics that increase the participants' repertoire of Git workflows: Bisection, Worktrees, Submodules, Large File Storage and Pre-commit Hooks. Additionally, we showcase invasive methods of modifying a Git repository via Rebase. | |
| Compact Course "Intermediate Topics in Version Control with Git"
Dr. Dominic Kempf
Applying version control can be a game changer for a collaborative research software project. However, even in projects that already successfully use Git, there is often room for improvement of the employed Git workflows. This workshop tries to delve into collaborative workflows using Git branches and discuss their strengths. Special emphasis is given to the resolution of merge conflicts that may be required in the process of dealing with diverging branches. | |
| Compact Course "Python Packaging"
Dr. Liam Keegan
In this course we will learn how to package a Python library, how to publish it on PyPI and on conda-forge, as well as look at more advanced topics like building pre-compiled wheels including c++ extensions using pybind11, and automatically publishing new releases using continuous integration and cibuildwheel. | |
| Compact Course "Generative AI for writing (research) software"
Dr. Inga Ulusoy
Generative AI is emerging as a major creative force that supports humans in content creation. Specifically trained models can support software developers with their software projects and lead to time savings and a shift in what aspects of generating software are more important on a day-to-day basis. In this course, we will learn how to set up and use AI tools in software development projects. Best practices in using such tools, as well as recommendations how to use them efficiently and safely will be introduced. | |
| Compact Course "Sustainability in Research Software for HPC"
Dr. Andreas Baer (KIT)
Maximal performance! This used to be the goal for research software for HPC, but sustainability is getting more and more traction and growing importance. This course targets two aspects contributing to sustainable research software for HPC clusters: Firstly, energy and carbon optimization in the usage is outlined to raise awareness and make the participants ready for future HPC systems with energy-budget-based resource grants or efficiency rewarding queuing systems as pioneered by Japans #1 supercomputer Fugaku. Secondly, sustainability in the development process of HPC research software is addressed, where productivity, code quality and carbon efficiency often go hand in hand. The course is specifically targeted to researchers using and developing HPC research software, in all career stages, irrespective of their usage type (e.g. physical simulations, data analysis, AI). It is intended as an interactive course, allowing plenty of time for discussion and exchange on this topic. | |
| Short Course "Getting started with generative AI coding tools"
Dr. Inga Ulusoy, Dr. Harald Mack
Generative AI is emerging as a major creative force that supports humans in content creation. AI coding tools can support software development on many levels. In this short course, participants will get started with using GitHub copilot in VSCode as effective coding tools. | |
| Compact Course "Python Best Practices"
Dr. Inga Ulusoy
Python is widely used in science and research, from data analysis and simulation to preparing publications. This course introduces practical habits and tools for writing readable, maintainable Python code. We will cover project setup, automated code formatting and checks, and the essentials of organizing code into an installable Python package. We will also introduce testing and type hints, explain common Python pitfalls, and explore useful programming patterns. Practical examples and hands-on exercises will help participants apply these techniques to their own projects. | |
| Compact Course "Simple interactive research sharing with R Shiny"
James Bowyer
Rather than just share pictures of your R research/graphs, R Shiny lets you turn your existing R analysis into an interactive web application that anyone can access through a link. With this live interface, your collaborators, grant reviewers, or other researchers can investigate the specific aspects they care about - like filtering by their genes of interest or adjusting parameters. We'll cover how to convert your current R files into Shiny apps, with practical information also relevant for Python Streamlit users on costs, maintenance time, and an overview of the process of hosting them online covered at the start so you can decide if this workshop is relevant for your purposes. This workshop is hands-on and works best when you send your R scripts to us one week in advance. You do not need to learn complicated web development - just the R you already know from the console and the process of deploying which works very similarly, and can all be completed inside of the "R studio" application. After this workshop, you will be able to share future projects the same way. | |
| Compact Course "Introduction to Python Testing"
Dr. Liam Keegan
An automated test suite makes it much easier to maintain, extend and debug your Python code. In this course we will learn how to write automated tests in Python using the pytest library. After introducing the key concepts, the majority of the course will be hands-on, writing and running tests. | |
| Compact Course "AI in research software: Best practices for developing and using ML models"
Dr. Inga Ulusoy, Dr. Harald Mack
The AI revolution is moving even more rapidly than the digital revolution and leads to the emergence of completely new tools and technologies that affect the scientific process. In this course, we will learn about data-based research software, tools and communities that are relevant in creating and sharing such software, and about best practices in training machine-learning models. Research software that is based on ML models requires an additional layer of best practices in the implementation, including testing of non-deterministic processes. Security aspects as well as bad examples are discussed to highlight the importance of adhering to a best practices code of conduct. | |
| Compact Course "Debugging in VSCode"
Dr. Dominic Kempf
Tired of debugging your code by randomly sprinkling print statements throughout your code? In this course we will learn the basics of debugging with an Integrated Development Environment (IDE): Setting breakpoints, stepping through code, inspecting variables, and evaluating expressions. We exercise these techniques on small code examples from the Python language. Afterwards, we will cover other languages and more complex debugging scenarios. We use Visual Studio Code (VSCode) as our IDE, but the taught concepts translate naturally to other IDEs. | |
| Compact Course "Python Performance Profiling"
Dr. Liam Keegan
To make your Python code run faster, you first need to understand where and why it is slow. In this course we will look at how to profile and benchmark the performance of Python code, as well as the compiled cpu and gpu code that gets invoked when you use libraries like numpy or pytorch. | |
| Compact Course "Expert Topics in Version Control with Git"
Dr. Dominic Kempf
Applying version control can be a game changer for a collaborative research software project. However, even in projects that already successfully use Git, there is often room for improvement of the employed Git workflows. This workshop explores some advanced topics that increase the participants' repertoire of Git workflows: Bisection, Worktrees, Submodules, Large File Storage and Pre-commit Hooks. Additionally, we showcase invasive methods of modifying a Git repository via Rebase. | |
| Compact Course "Intermediate Topics in Version Control with Git"
Dr. Dominic Kempf
Applying version control can be a game changer for a collaborative research software project. However, even in projects that already successfully use Git, there is often room for improvement of the employed Git workflows. This workshop tries to delve into collaborative workflows using Git branches and discuss their strengths. Special emphasis is given to the resolution of merge conflicts that may be required in the process of dealing with diverging branches. | |
| Compact Course "The Unix Shell + Version Control with Git"
Dr. Dominic Kempf
The Unix shell is a powerful tool that allows people to do complex things with just a few keystrokes. More importantly, it helps them combine existing programs in new ways and automate repetitive tasks so they aren't typing the same things over and over again. Use of the shell is fundamental to using a wide range of other powerful tools and computing resources. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers.
Version control is the lab notebook of the digital world: it is used to keep track of what was done and to collaborate with other people. Its use is the state of the art in software development projects of all scales. However, it is not limited to software: books, papers, small data sets, and anything that changes over time or needs to be shared can and should be stored in a version control system. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers. | |
| Compact Course "The Unix Shell + Version Control with Git"
Dr. Dominic Kempf
The Unix shell is a powerful tool that allows people to do complex things with just a few keystrokes. More importantly, it helps them combine existing programs in new ways and automate repetitive tasks so they aren't typing the same things over and over again. Use of the shell is fundamental to using a wide range of other powerful tools and computing resources. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers.
Version control is the lab notebook of the digital world: it is used to keep track of what was done and to collaborate with other people. Its use is the state of the art in software development projects of all scales. However, it is not limited to software: books, papers, small data sets, and anything that changes over time or needs to be shared can and should be stored in a version control system. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers. | |
| Compact Course "Building software with CMake"
Dr. Dominic Kempf
CMake has emerged as the de facto standard tool to manage the build process of software developed in compiled languages. It allows to describe the complex build configuration in a descriptive manner and thus enables flexibility, portability, scalability and robustness of the build process. In this course, we will first cover CMake from the end user perspective and learn how to build software that already provides a CMake build system. In the second part, we will dive into how to write a CMake build system for our own software. Special emphasis is put on explaining the principles of "Modern CMake" - a set of best practices to get more milage out of the tool. | |
| Compact Course "Effective Software Testing"
Dr. Liam Keegan
A good test suite makes extending, maintaining and debugging a codebase both easier and faster. In this course we will look at the different kinds of tests, and understand how to write good tests. We will also cover different testing strategies, such as test-driven-design when writing new code, or acceptance testing when working with legacy code that doesn't have a good test suite. Code samples will use the Python testing framework pytest but the concepts also apply to other frameworks and languages. | |
| Block Course "Scientific Software Development"
Dr. Inga Ulusoy
In this course, you will learn how to develop scientific software in a way that enables reproducible research and sustainable software. Sustainable scientific software leaves room for further, subsequent implementations and method development, and saves time and effort in the long run; additionally, a sustainable approach follows good scientific practice through making results reproducible. This course is aimed at researchers, doctoral and master students who develop scientific software to carry out their research. | |
| Compact Course "Python Packaging"
Dr. Liam Keegan
In this course we will learn how to package a Python library, how to publish it on PyPI and on conda-forge, as well as look at more advanced topics like building pre-compiled wheels including c++ extensions using pybind11, and automatically publishing new releases using continuous integration and cibuildwheel. | |
| Compact Course "AI in research software: Best practices for developing and using ML models"
Dr. Inga Ulusoy
The AI revolution is moving even more rapidly than the digital revolution and leads to the emergence of completely new tools and technologies that affect the scientific process. In this course, we will learn about data-based research software, tools and communities that are relevant in creating and sharing such software, and about best practices in training machine-learning models. Research software that is based on ML models requires an additional layer of best practices in the implementation, including testing of non-deterministic processes. Security aspects as well as bad examples are discussed to highlight the importance of adhering to a best practices code of conduct. | |
| Compact Course "Data Exploration with Python and Jupyter"
Dr. Liam Keegan
Jupyter notebooks are a great tool for exploring and interacting with data using the Python programming language and its rich ecosystem of libraries. In this course we will cover basic usage of the Pandas library to download a dataset, explore its contents, clean up missing or invalid data, filter the data according to different criteria, and plot visualizations of the data. | |
| Compact Course "Continuous Integration with Github Actions"
Dr. Dominic Kempf
Continuous Integration (CI) is one of the cornerstones of agile development processes: Before changes are included into the mainline, a number of tests is run automatically to ensure the quality of the software. In this course, we explain how this process is implemented on GitHub.com (GitHub Actions). After a general introduction, participants will work on setting up Github Actions for their own projects. The SSC is available for follow-up consultation work on the CI workflows developed during this course. | |
| Compact Course "Containers in Science: Using Docker and Singularity"
Dr. Dominic Kempf
Container technologies (e.g. Docker containers) have emerged as a fundamental tool of the cloud computing era. In scientific applications, containerization is used to encapsulate the complex execution environment of research software with a number of goals in mind: Setting up user landscapes for Continuous Integration testing, ensuring reproducibility of execution environments and packaging code to run on an HPC system. The workshop involves live coding sessions where participants exercise the learned commands on their own computers. | |
| Compact Course "The Unix Shell + Version Control with Git"
Dr. Dominic Kempf
The Unix shell is a powerful tool that allows people to do complex things with just a few keystrokes. More importantly, it helps them combine existing programs in new ways and automate repetitive tasks so they aren't typing the same things over and over again. Use of the shell is fundamental to using a wide range of other powerful tools and computing resources. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers.
Version control is the lab notebook of the digital world: it is used to keep track of what was done and to collaborate with other people. Its use is the state of the art in software development projects of all scales. However, it is not limited to software: books, papers, small data sets, and anything that changes over time or needs to be shared can and should be stored in a version control system. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers. | |
| Compact Course "Generative AI for writing (research) software"
Dr. Inga Ulusoy
Generative AI is emerging as a major creative force that supports humans in content creation. Specifically trained models can support software developers with their software projects and lead to time savings and a shift in what aspects of generating software are more important on a day-to-day basis. In this course, we will learn how to set up and use AI tools in software development projects. Best practices in using such tools, as well as recommendations how to use them efficiently and safely will be introduced. | |
| Compact Course "Python Best Practices"
Dr. Inga Ulusoy
Python is widely used in science and research, from data analysis and simulation to preparing publications. This course introduces practical habits and tools for writing readable, maintainable Python code. We will cover project setup, automated code formatting and checks, and the essentials of organizing code into an installable Python package. We will also introduce testing and type hints, explain common Python pitfalls, and explore useful programming patterns. Practical examples and hands-on exercises will help participants apply these techniques to their own projects. | |
| Compact Course "Introduction to Python Testing"
Dr. Liam Keegan
An automated test suite makes it much easier to maintain, extend and debug your Python code. In this course we will learn how to write automated tests in Python using the pytest library. After introducing the key concepts, the majority of the course will be hands-on, writing and running tests. | |
| Compact Course "Effective Software Testing"
Dr. Liam Keegan
A good test suite makes extending, maintaining and debugging a codebase both easier and faster. In this course we will look at the different kinds of tests, and understand how to write good tests. We will also cover different testing strategies, such as test-driven-design when writing new code, or acceptance testing when working with legacy code that doesn't have a good test suite. Code samples will use the Python testing framework pytest but the concepts also apply to other frameworks and languages. | |
| Compact Course "Data Exploration with Python and Jupyter"
Dr. Liam Keegan
Jupyter notebooks are a great tool for exploring and interacting with data using the Python programming language and its rich ecosystem of libraries. In this course we will cover basic usage of the Pandas library to download a dataset, explore its contents, clean up missing or invalid data, filter the data according to different criteria, and plot visualizations of the data. | |
| Compact Course "AI in research software: Best practices for developing and using ML models"
Dr. Inga Ulusoy
The AI revolution is moving even more rapidly than the digital revolution and leads to the emergence of completely new tools and technologies that affect the scientific process. In this course, we will learn about data-based research software, tools and communities that are relevant in creating and sharing such software, and about best practices in training machine-learning models. Research software that is based on ML models requires an additional layer of best practices in the implementation, including testing of non-deterministic processes. Security aspects as well as bad examples are discussed to highlight the importance of adhering to a best practices code of conduct. | |
| Compact Course "Generative AI for writing (research) software"
Dr. Inga Ulusoy
Generative AI is emerging as a major creative force that supports humans in content creation. Specifically trained models can support software developers with their software projects and lead to time savings and a shift in what aspects of generating software are more important on a day-to-day basis. In this course, we will learn how to set up and use AI tools in software development projects. Best practices in using such tools, as well as recommendations how to use them efficiently and safely will be introduced. | |
| Compact Course "Python Best Practices"
Dr. Inga Ulusoy
Python is widely used in science and research, from data analysis and simulation to preparing publications. This course introduces practical habits and tools for writing readable, maintainable Python code. We will cover project setup, automated code formatting and checks, and the essentials of organizing code into an installable Python package. We will also introduce testing and type hints, explain common Python pitfalls, and explore useful programming patterns. Practical examples and hands-on exercises will help participants apply these techniques to their own projects. | |
| Compact Course "Expert Topics in Version Control with Git"
Dr. Dominic Kempf
Applying version control can be a game changer for a collaborative research software project. However, even in projects that already successfully use Git, there is often room for improvement of the employed Git workflows. This workshop explores some advanced topics that increase the participants' repertoire of Git workflows: Bisection, Worktrees, Submodules, Large File Storage and Pre-commit Hooks. Additionally, we showcase invasive methods of modifying a Git repository via Rebase. | |
| Compact Course "Intermediate Topics in Version Control with Git"
Dr. Dominic Kempf
Applying version control can be a game changer for a collaborative research software project. However, even in projects that already successfully use Git, there is often room for improvement of the employed Git workflows. This workshop tries to delve into collaborative workflows using Git branches and discuss their strengths. Special emphasis is given to the resolution of merge conflicts that may be required in the process of dealing with diverging branches. | |
| Compact Course "The Unix Shell + Version Control with Git"
Dr. Dominic Kempf
The Unix shell is a powerful tool that allows people to do complex things with just a few keystrokes. More importantly, it helps them combine existing programs in new ways and automate repetitive tasks so they aren't typing the same things over and over again. Use of the shell is fundamental to using a wide range of other powerful tools and computing resources. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers.
Version control is the lab notebook of the digital world: it is used to keep track of what was done and to collaborate with other people. Its use is the state of the art in software development projects of all scales. However, it is not limited to software: books, papers, small data sets, and anything that changes over time or needs to be shared can and should be stored in a version control system. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers. | |
| Compact Course "Python Packaging"
Dr. Liam Keegan
In this course we will learn how to package a Python library, how to publish it on PyPI and on conda-forge, as well as look at more advanced topics like building pre-compiled wheels including c++ extensions using pybind11, and automatically publishing new releases using continuous integration and cibuildwheel. | |
| Compact Course "Python Packaging"
Dr. Liam Keegan
In this course we will learn how to package a Python library, how to publish it on PyPI and on conda-forge, as well as look at more advanced topics like building pre-compiled wheels including c++ extensions using pybind11, and automatically publishing new releases using continuous integration and cibuildwheel. | |
| Block Course "Scientific Software Development"
Dr. Inga Ulusoy
In this course, you will learn how to develop scientific software in a way that enables reproducible research and sustainable software. Sustainable scientific software leaves room for further, subsequent implementations and method development, and saves time and effort in the long run; additionally, a sustainable approach follows good scientific practice through making results reproducible. This course is aimed at researchers, doctoral and master students who develop scientific software to carry out their research. | |
| Compact Course "The Unix Shell + Version Control with Git"
Dr. Dominic Kempf
The Unix shell is a powerful tool that allows people to do complex things with just a few keystrokes. More importantly, it helps them combine existing programs in new ways and automate repetitive tasks so they aren't typing the same things over and over again. Use of the shell is fundamental to using a wide range of other powerful tools and computing resources. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers.
Version control is the lab notebook of the digital world: it is used to keep track of what was done and to collaborate with other people. Its use is the state of the art in software development projects of all scales. However, it is not limited to software: books, papers, small data sets, and anything that changes over time or needs to be shared can and should be stored in a version control system. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers. | |
| Compact Course "Introduction to Python Testing"
Dr. Liam Keegan
An automated test suite makes it much easier to maintain, extend and debug your Python code. In this course we will learn how to write automated tests in Python using the pytest library. After introducing the key concepts, the majority of the course will be hands-on, writing and running tests. | |
| Compact Course "The Unix Shell + Version Control with Git"
Dr. Dominic Kempf
The Unix shell is a powerful tool that allows people to do complex things with just a few keystrokes. More importantly, it helps them combine existing programs in new ways and automate repetitive tasks so they aren't typing the same things over and over again. Use of the shell is fundamental to using a wide range of other powerful tools and computing resources. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers.
Version control is the lab notebook of the digital world: it is used to keep track of what was done and to collaborate with other people. Its use is the state of the art in software development projects of all scales. However, it is not limited to software: books, papers, small data sets, and anything that changes over time or needs to be shared can and should be stored in a version control system. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers. | |
| Compact Course "Python Best Practices"
Dr. Inga Ulusoy
Python is widely used in science and research, from data analysis and simulation to preparing publications. This course introduces practical habits and tools for writing readable, maintainable Python code. We will cover project setup, automated code formatting and checks, and the essentials of organizing code into an installable Python package. We will also introduce testing and type hints, explain common Python pitfalls, and explore useful programming patterns. Practical examples and hands-on exercises will help participants apply these techniques to their own projects. | |
| Compact Course "The Unix Shell + Version Control with Git"
Dr. Dominic Kempf
The Unix shell is a powerful tool that allows people to do complex things with just a few keystrokes. More importantly, it helps them combine existing programs in new ways and automate repetitive tasks so they aren't typing the same things over and over again. Use of the shell is fundamental to using a wide range of other powerful tools and computing resources. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers.
Version control is the lab notebook of the digital world: it is used to keep track of what was done and to collaborate with other people. Its use is the state of the art in software development projects of all scales. However, it is not limited to software: books, papers, small data sets, and anything that changes over time or needs to be shared can and should be stored in a version control system. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers. | |
| Compact Course "A short tour of sustainable software development"
Dr. Dominic Kempf
The course will give a brief overview of best practices for the sustainable development of research software.Areas covered are e.g. version control, development workflows, licensing, documentation, software testing, CI/CD, packaging, static code analysis, clean code. The course will emphasize the importance of these topics for the development process, give opinionated tooling recommendations and share experiences. The primary goal of the course is to enable the participants to formulate a roadmap of courses and self-learning activities to further improve their software development skills. | |
| Compact Course "Effective Software Testing"
Dr. Liam Keegan
A good test suite makes extending, maintaining and debugging a codebase both easier and faster. In this course we will look at the different kinds of tests, and understand how to write good tests. We will also cover different testing strategies, such as test-driven-design when writing new code, or acceptance testing when working with legacy code that doesn't have a good test suite. Code samples will use the Python testing framework pytest but the concepts also apply to other frameworks and languages. | |
| Block Course "Scientific Software Development"
Dr. Inga Ulusoy
In this course, you will learn how to develop scientific software in a way that enables reproducible research and sustainable software. Sustainable scientific software leaves room for further, subsequent implementations and method development, and saves time and effort in the long run; additionally, a sustainable approach follows good scientific practice through making results reproducible. This course is aimed at researchers, doctoral and master students who develop scientific software to carry out their research. | |
| Compact Course "Containers in Science: Using Docker and Singularity"
Dr. Dominic Kempf
Container technologies (e.g. Docker containers) have emerged as a fundamental tool of the cloud computing era. In scientific applications, containerization is used to encapsulate the complex execution environment of research software with a number of goals in mind: Setting up user landscapes for Continuous Integration testing, ensuring reproducibility of execution environments and packaging code to run on an HPC system. The workshop involves live coding sessions where participants exercise the learned commands on their own computers. | |
| Compact Course "Python Best Practices"
Dr. Inga Ulusoy
Python is widely used in science and research, from data analysis and simulation to preparing publications. This course introduces practical habits and tools for writing readable, maintainable Python code. We will cover project setup, automated code formatting and checks, and the essentials of organizing code into an installable Python package. We will also introduce testing and type hints, explain common Python pitfalls, and explore useful programming patterns. Practical examples and hands-on exercises will help participants apply these techniques to their own projects. | |
| Compact Course "Open Source Licensing"
Dr. Dominic Kempf
Software licenses set the legal terms about using and reusing software. For a software project to be usable by others, a license is absolutely required. The course will introduce popular open source licenses and discuss the differences between them. Using real world examples, we study the licensing constraints that may arise from distributing a software project including its dependencies (both for compiled and interpreted languages). Furthermore, the course gives an overview of licenses for documentation and data. This course intends to enable participants to make their own informed decisions - no legal advice can be given during the course. | |
| Compact Course "High Performance C++"
Dr. Liam Keegan
In this course we will look at how the choice of algorithms, data structures and hardware influences the performance of our C++ applications. We will cover some performance best practices which are always applicable, as well as some possible optimizations for more specific scenarios. We will also discuss when not to optimize, for example sacrificing readability and maintainability for a minimal performance gain, or preventing the compiler from doing a different and possibly better optimization. Finally we will apply this knowledge to optimize example code in a series of hands-on exercises. | |
| Compact Course "The Unix Shell + Version Control with Git"
Dr. Dominic Kempf
The Unix shell is a powerful tool that allows people to do complex things with just a few keystrokes. More importantly, it helps them combine existing programs in new ways and automate repetitive tasks so they aren't typing the same things over and over again. Use of the shell is fundamental to using a wide range of other powerful tools and computing resources. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers.
Version control is the lab notebook of the digital world: it is used to keep track of what was done and to collaborate with other people. Its use is the state of the art in software development projects of all scales. However, it is not limited to software: books, papers, small data sets, and anything that changes over time or needs to be shared can and should be stored in a version control system. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers. | |
| Compact Course "Data Exploration with Python and Jupyter"
Dr. Liam Keegan
Jupyter notebooks are a great tool for exploring and interacting with data using the Python programming language and its rich ecosystem of libraries. In this course we will cover basic usage of the Pandas library to download a dataset, explore its contents, clean up missing or invalid data, filter the data according to different criteria, and plot visualizations of the data. | |
| Block Course "Scientific Software Development"
Dr. Inga Ulusoy
In this course, you will learn how to develop scientific software in a way that enables reproducible research and sustainable software. Sustainable scientific software leaves room for further, subsequent implementations and method development, and saves time and effort in the long run; additionally, a sustainable approach follows good scientific practice through making results reproducible. This course is aimed at researchers, doctoral and master students who develop scientific software to carry out their research. | |
| Compact Course "C++ Performance Profiling"
Dr. Liam Keegan
We use compiled languages like C++, Rust or Fortran to get good performance, so measuring and understanding the performance characteristics of our code is vital, for example to identify bottlenecks or to determine if a change to the code actually improves the performance. In this course we will cover different ways to profile and benchmark the performance of our code, and discuss the pros and cons of each method. Code examples will be in C++ but the profiling applies to most compiled languages. | |
| Compact Course "Containers in Science: Using Docker and Singularity"
Dr. Dominic Kempf
Container technologies (e.g. Docker containers) have emerged as a fundamental tool of the cloud computing era. In scientific applications, containerization is used to encapsulate the complex execution environment of research software with a number of goals in mind: Setting up user landscapes for Continuous Integration testing, ensuring reproducibility of execution environments and packaging code to run on an HPC system. The workshop involves live coding sessions where participants exercise the learned commands on their own computers. | |
| Compact Course "The Unix Shell + Version Control with Git"
Dr. Dominic Kempf
The Unix shell is a powerful tool that allows people to do complex things with just a few keystrokes. More importantly, it helps them combine existing programs in new ways and automate repetitive tasks so they aren't typing the same things over and over again. Use of the shell is fundamental to using a wide range of other powerful tools and computing resources. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers.
Version control is the lab notebook of the digital world: it is used to keep track of what was done and to collaborate with other people. Its use is the state of the art in software development projects of all scales. However, it is not limited to software: books, papers, small data sets, and anything that changes over time or needs to be shared can and should be stored in a version control system. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers. | |
| Compact Course "Data Exploration with Python and Jupyter"
Dr. Liam Keegan
Jupyter notebooks are a great tool for exploring and interacting with data using the Python programming language and its rich ecosystem of libraries. In this course we will cover basic usage of the Pandas library to download a dataset, explore its contents, clean up missing or invalid data, filter the data according to different criteria, and plot visualizations of the data. | |
| Compact Course "Containers in Science: Using Docker and Singularity"
Dr. Dominic Kempf
Container technologies (e.g. Docker containers) have emerged as a fundamental tool of the cloud computing era. In scientific applications, containerization is used to encapsulate the complex execution environment of research software with a number of goals in mind: Setting up user landscapes for Continuous Integration testing, ensuring reproducibility of execution environments and packaging code to run on an HPC system. The workshop involves live coding sessions where participants exercise the learned commands on their own computers. | |
| Compact Course "The Unix Shell + Version Control with Git"
Dr. Dominic Kempf
The Unix shell is a powerful tool that allows people to do complex things with just a few keystrokes. More importantly, it helps them combine existing programs in new ways and automate repetitive tasks so they aren't typing the same things over and over again. Use of the shell is fundamental to using a wide range of other powerful tools and computing resources. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers.
Version control is the lab notebook of the digital world: it is used to keep track of what was done and to collaborate with other people. Its use is the state of the art in software development projects of all scales. However, it is not limited to software: books, papers, small data sets, and anything that changes over time or needs to be shared can and should be stored in a version control system. The course will include hands-on live coding sessions where participants exercise the learned commands on their own computers. | |
| Block Course "Scientific Software Development"
Dr. Inga Ulusoy
In this course, you will learn how to develop scientific software in a way that enables reproducible research and sustainable software. Sustainable scientific software leaves room for further, subsequent implementations and method development, and saves time and effort in the long run; additionally, a sustainable approach follows good scientific practice through making results reproducible. This course is aimed at researchers, doctoral and master students who develop scientific software to carry out their research. | |
