Our upcoming courses at Helmholtz Munich
Date: 24, 25 June 2025
Time: 09:00 - 17:00
Format: Campus Neuherberg
Registration: CaMS
In the Introduction to Machine Learning course, we delve into the practical application of fundamental machine learning techniques for data analysis using Python. This course is designed for individuals who want to start using machine learning for data analysis, focusing less on traditional statistics and more on predictive modeling to classify data or predict outcomes. The course is taught interactively with live coding using Jupyter Notebook.
By the end of the course, you will be able to confidently select and utilize basic machine learning techniques, effectively interpret your findings, and apply them to real-world scenarios.
Prerequisites: Programming skills with Python, e.g. course Introduction to Python. Basic understanding of statistical methods, in particular regression analysis, is recommended, e.g. course Introduction to Statistics.
Date: 1, 2 July 2025
Time: 9:00 - 17:00
Format: Campus Neuherberg
Registration: CaMS
“Introduction to R” provides a foundation for coding with the statistical programming language R. The course is designed for applied researchers with no previous programming skills. In this course you will learn the basics of coding in R. In particular, you will learn how to read and manipulate datasets. These skills are necessary for performing any subsequent statistical analyses in R.
Prerequisites: None
Date: 08, 09, 15, 16 July 2025
Time: 9:00 - 17:00
Format: Campus Neuherberg
Registration: CaMS
“Introduction to Statistics” is a foundational course in statistical analysis for scientists and practitioners. This course covers descriptive statistics, classical statistical tests (t-test, Wilcoxon/Mann-Whitney-U test, ANOVA, etc), and linear regression and its extensions. All methods are explained in an applied setting. By the end of the course, you will be able to identify appropriate statistical methods, apply them, and interpret your results.
Prerequisites: Basic skills in programming with R, e.g. course “Introduction to R”
Date: 10 July 2025
Time: 09:00 - 13:00
Format: Campus Neuherberg
Registration: CaMS
“Reproducible and Open Research” provides a broad overview on different aspects of open research and reproducibility. This includes the fields of technical, statistical and computational reproducibility. With a focus on the latter two aspects. The idea of this course is to introduce general concepts of reproducibility and open science to everyone, but with a focus on early career researchers. The course consists of lessons on different aspects of open and reproducible research and offers the opportunity to discuss experiences and expectations on this topic. Various other features of Open Science will also be discussed. Furthermore, some hand-on examples of how to implement these methods in your daily work are provided.
Prerequisites: None. However, basic knowledge in statistics and programming is advantageous.
Date: 10 July 2025
Time: 13:30 - 17:00
Format: Campus Neuherberg
Registration: CaMS
“Shiny” is a powerful tool providing more than just static graphics or tables to readers. It enables us to directly combine R code/outputs with the writing of interactive html pages. The user can modify all kinds of features, for example selecting specific groups, adding further covariates, or simply playing around to discover more features step-by-step. In this course we combine some short introduction on how shiny works with hands-on exercises.
Prerequisites: Programming skills with R, e.g. course Introduction to R. Basic knowledge on applying ggplot2 functions (e.g. course Graphics with R) and using RMarkdown (e.g. course RMarkdown) is advantageous but not mandatory.
Date: 11 July 2025
Time: 9:00 - 12:30
Format: Campus Neuherberg
Registration: CaMS
Data visualization allows us to represent and understand information in a fast and intuitive manner. What makes great charts great? And what makes bad charts bad, or even sometimes misleading? It is easy to view charts as factual and impartial, but every chart tells a story and highlights different aspects of the underlying data. Through a series of real-life examples, we will discuss the importance of clear and deliberate data visualization, which ingredients we need to combine to create clear and precise visualizations and learn how communicate as clearly through our charts as in our writing.
Please consider this seminar was part of the “Data Visualization Workshop” in 2022 & 2023.
If you would like to learn how to code more advanced graphics in R, please check out our course “Graphics with R”. If you would like to learn which plots to use for what kind of data, we recommend our course “Introduction to Statistics” or our advanced statistics courses.
Date: 17, 18 July 2025
Time: 9:00 - 17:00
Format: Campus Neuherberg
Registration: CaMS
In the Advanced Methods in Machine Learning course, we go beyond the most basic approaches used in Machine Learning for classification and regression. We will explore Support Vector Machines, ensemble methods like Random Forests and Boosting, and introduce the fundamentals of Deep Learning using convolutional networks. Furthermore, we also cover sampling techniques for robust model evaluation, measuring estimation confidence, and handling imbalanced datasets. By the end, you will have an overview of some of the most important techniques in Machine Learning, can apply these methods in real-world scenarios, and have a basic understanding how Deep Learning can be applied using PyTorch.
Prerequisites: Python programming skill, as taught in the Introduction to Python course and basic knowledge of Machine Learning and model evaluation, e.g. Introduction to Machine Learning course.
The plan for 2025 is available HERE. Registration opens some weeks prior to the course, please check CaMS for details. Please consider that dates might change slightly throughout the year.
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These courses are designed for employees of Helmholtz Munich. Please use CaMS for registration. For questions please contact us via email.
For employees of other Helmholtz centers we offer similar courses at HIDA.