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This is a PhD-course in applied statistical learning, ie. about using statistical techniques, such as modelling and prediction, to analyse real datasets, and making correct interpretations and conclusions. AimThe course begins with an overview of basic data wrangling and visualisation, with a focus on the student's ability to identify and illustrate important features of the data.  Then important

https://www.compute.lu.se/article/data-analysis-statistical-learning-and-visualization-fmsf90f-vt-2023-75-ects - 2026-09-05

Understanding and rationalizing chemical reactions, their mechanism, and the relation between molecular structure and function is key to today's science. It is a difficult task for experiments alone and computational methods are often used to complement experiment. AimThis course covers basic theory and practical application of computational methods and programs widely used in chemistry and molecu

https://www.compute.lu.se/article/computational-chemistry-vt-2023-75-ects - 2026-09-05

The aim of this course is to introduce students to the Jupyter Notebook which is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. ObjectivesThe aim of this course is to introduce students to the Jupyter Notebook which is an open-source web application that allows you to create and share documents th

https://www.compute.lu.se/article/reproducible-and-interactive-data-analysis-and-modelling-using-jupyter-notebooks-natf017-ht2022 - 2026-09-05

The course discusses programming techniques required to efficiently utilise parallel computing in a computational research project in science or engineering. ObjectiveThe course discusses programming techniques required to efficiently utilise parallel computing in a computational research project in science or engineering. The course will discuss shared memory and distributed memory parallelisatio

https://www.compute.lu.se/article/parallel-programming-hpc-systems-ntf010f-ht-2022-75-ects - 2026-09-05

Stochastic Differential Equations (SDEs) have become a standard tool to model differential equation systems subject to noise. Applications range from Neuroscience or Polymeric Chemistry to Finance or Mechanical Engineering. Stochastic Differential Equations (SDEs) have become a standard tool to model differential equation systems subject to noise. Applications range from Neuroscience or Polymeric

https://www.compute.lu.se/article/advanced-material-stochastic-numerics-nma008f-ht-2022 - 2026-09-05

The purpose of the course is to provide basic knowledge of the programming language R to facilitate independent future use of applications written and / or implemented in this language, such as statistical analysis programs. ObjectiveThe purpose of the course is to provide basic knowledge of the programming language R to facilitate independent future use of applications written and / or implemente

https://www.compute.lu.se/article/basic-data-handling-and-visualization-r-ht2022-15-ects - 2026-09-05

COMPUTE Environment event, "Working with Git", given by Emma Söderberg from Computer Science. 23rd October, 13-15. Register below. Thursday, October 23rd, 13-15 in MH:228, Centre of MathematicsWe will have this years third COMPUTE Environment event, "Working with Git", given by Emma Söderberg from Computer Science.Git is a widely used system for version control. It is commonly used in software dev

https://www.compute.lu.se/article/working-git - 2026-09-05

Stochastic Differential Equations (SDEs) have become a quite standard tool to model differential equation systems subject to noise. Applications range from Neuroscience or Polymeric Chemistry to Finance or Mechanical Engineering. ObjectiveStochastic Differential Equations (SDEs) have become a quite standard tool to model differential equation systems subject to noise. Applications range from Neuro

https://www.compute.lu.se/article/introduction-stochastic-numerics-ht2022-3-ects - 2026-09-05

This course is intended for students with basic knowledge of programming in any language who would like to learn the techniques of scientific programming. ObjectiveThis course is intended for students with basic knowledge of programming in any language who would like to learn the techniques of scientific programming. The course covers scientific programming in Python, including writing numerical c

https://www.compute.lu.se/article/scientific-computing-python-and-fortran-ht2022-75-ects - 2026-09-05

The aim of the course is to give an introduction to computational programming in Python for students without any previous programming knowledge. ObjectiveThe aim of the course is to give an introduction to computational programming in Python for students without any previous programming knowledge. There is a strong orientation towards computational mathematics. Python is a modern scripting languag

https://www.compute.lu.se/article/computational-programming-python-numa01f-ht2022-75-ects - 2026-09-05

The aim of the course is to give necessary knowledge of digital image analysis for further research within the area and to be able to use digital image analysis within other research areas such as computer graphics, image coding, video coding and industrial image processing problems. ObjectiveThe aim of the course is to give necessary knowledge of digital image analysis for further research within

https://www.compute.lu.se/article/image-analysis-vt2022-75-ects - 2026-09-05

This course aims to provide a basic introduction to R, preparing students for using R in their own research and for additional courses that use R. ObjectiveThis course aims to provide a basic introduction to R, preparing students for using R in their own research and for additional courses that use R. The course will use a combination of brief lectures and tutorials where the students will work on

https://www.compute.lu.se/article/introduction-r-vt2022-15-ects - 2026-09-05

This course is intended for students with intermediate knowledge of programming in Python and basic knowledge of partial differential equations (PDEs) who would like to learn techniques how to solve such problems numerically. ObjectiveThis course is intended for students with intermediate knowledge of programming in Python and basic knowledge of partial differential equations (PDEs) who would like

https://www.compute.lu.se/article/solving-pdes-dune-fem-vt2022-30-ects - 2026-09-05

The aim of the course is to give an introduction to computational programming in Python for students without any previous programming knowledge. ObjectiveThe aim of the course is to give an introduction to computational programming in Python for students without any previous programming knowledge. There is a strong orientation towards computational mathematics. Python is a modern scripting languag

https://www.compute.lu.se/article/computational-programming-python-ht2021-75-ects - 2026-09-05

The course discusses numerical methods about coupled problems, where different mathematical models for different physics are coupled along an interface. ObjectiveThe course discusses numerical methods about coupled problems, where different mathematical models for different physics are coupled along an interface. Examples are ocean-atmosphere interaction, fluid-structure interaction in wind turbin

https://www.compute.lu.se/article/numerical-analysis-coupled-problems-ht2021-75-ects - 2026-09-05

This course will teach knowledge and practical experience of how to develop software together in a team. The focus is on practical experience of methods and tools suitable for a smaller software project with one developer team. ObjectivesThis course will teach knowledge and practical experience of how to develop software together in a team. The focus is on practical experience of methods and tools

https://www.compute.lu.se/article/agile-software-development-ht2021-75-ects - 2026-09-05

The aim of this course is to introduce students to common deep learnings architectues such as multi-layer perceptrons, convolutional neural networks and recurrent models such as the LSTM. Course descriptionRecent development in machine learning have led to a surge of interest in artificial neural networks (ANN). New efficient algorithms and increasingly powerful hardware has made it possible to cr

https://www.compute.lu.se/article/introduction-deep-learning-ht2021-45-ects - 2026-09-05

Issue #8 - 2025 Huminfra is a Swedish national infrastructure supporting digital and experimental research in the Humanities by providing users with a single entry point for finding existing Swedish materials and research tools, as well as developing national method courses.LinksHuminfra Newsletter #8 - 2025Huminfra home page

https://www.compile.lu.se/article/huminfra-newsletter-0 - 2026-09-05

No 46, 8 October 2025 In this newsletter we advertise a wide variety of NAISS training events, scheduled for the autumn term.   Since the last time, we added an introduction to the Linux command line and the Programming Formalism course.An overview on our events is available on the NAISS website.OverviewNAISS trainingOnline training workshop: Basic Singularity/Apptainer workshop, 13 October, 2025O

https://www.compile.lu.se/article/naiss-training-newsletter-1 - 2026-09-05

No 48, 7 November 2025 In this newsletter we advertise a wide variety of NAISS training events, scheduled for the autumn term.An overview on our events is available on the NAISS training page (NAISS).OverviewNAISS trainingOnline workshop: Log in and Transfer Files to/from HPC Clusters, 14 November, 2025Online hackathon: Bianca In-Depth: Improve Your Handling of Sensitive Research Data, 18 November

https://www.compile.lu.se/article/naiss-training-newsletter-2 - 2026-09-05