Machine learning affects our daily life in various aspects: online shopping, music and movie suggestions or asking your home assistant for the current weather. Over the last decades, the amount of data has skyrocketed in almost every professional domain. This prompts for efficient computer- and statistics-driven analysis and predictive modeling to extract useful information and guide important decisions.

Machine learning can be performed in all major programming languages, but Python has established itself as a standard. In this course, you will learn the fundamentals of machine learning (data collection, cleaning, modeling and prediction) through hands-on exercises on real-world data sets. You will understand the differences between supervised and unsupervised learning and get to know common models and algorithms. Furthermore, you will be able to evaluate the performance of the trained models.

In the world of machine learning, it is important to critically scrutinize the ethical implications of the application of your models. Hence, we will discuss the challenges and limitations of modern machine learning.

Requirements: Basic knowledge of Python is required, e.g. via a successful completion of our 'Introduction to programming with Python' course, or similar. We will use our own server platform for the course, therefore no additional installation of software is needed.

Aim:
You will learn to visually communicate your complex research ideas and results so your messages are effortlessly understood by any specific audience (scientists or non-scientists). We will not focus on aesthetics but on how understanding human visual perception can inform your design decision for better comprehension of your scientific images, posters, and slides. You will also design a graphical abstract of your research, discuss it with peer scientists in a group exercise, and get actionable advice and feedback on your own materials. It is an immersive workshop, comprehensive, structured, memorable, easy to follow, useful and fun. More at https://www.seyens.com

Contents & Method:
The training is offered as blended learning that combines a self-study module and a live online workshop. All participants get 12 month access to all materials.

1. Self-study via an online platform (6-8 hours of engaging video content & a useful assignment):
1.1. Communicating with scientific vs non-scientific audiences
1.2. Visual perception and what humans find intuitive
1.3. Layout: simplifying comprehension through structured layout
1.4. Eye-flow: effortlessly guide the audience through the design
1.5. Colors: how to amplify, not ‘fancify’
1.6. Typography for legibility, structure and aesthetics
1.7. Digital images in science: the optimal use of vector and raster images
1.8. Slides that amplify messages and don't distract when presenting
1.9. Posters: strategy and process for creating posters that attract and explain
1.10. Homework: participants submit images and slides to the trainer to receive feedback
2. Live Online Workshop (April 10, 2025, 9 am – 1 pm via Zoom, interactive and hands-on)
2.1. Recap of fundamentals and Q&A: trainer facilitates an effective recap of lessons learned in self-study module and answers all further questions.
2.2. Exercises & group work: participants draw a graphical abstract of their research and share their posters and we form groups so everyone gives and receives informed feedback.

Discussion on pre-submitted materials: participants receive actionable suggestions on how to improve their own images and slides from the trainer and on posters from fellow researchers.

Fever has long been a threatening and inescapable feature of the human condition; as the German poet Friedrich Hebbel noted in 1860, “He who would live must hazard the fever.” For centuries, “fever” denoted a disease marked by various sensations – heat, but also an altered pulse, or delirium. Only from the 1840s onward was fever reduced to quantifiable temperature, and reframed as a symptom of diverse diseases, which from the late 1800s onward came to be associated with specific pathogens. Today, the re-emergence of old and the emergence of new infectious diseases rank among the principal challenges facing humankind. This multidisciplinary summer school brings together perspectives from the life and natural sciences as well as the humanities to re-examine the multifaceted nature of fever.

Topics include epidemics and pandemics of febrile illnesses; their prevention, including vaccines and their societal acceptance (or resistance); the sensory register of fever, including but exceeding heat and temperature, e.g. its production, theorisation, and effects on the body; disease causation, e.g. through pathogens and vectors; and febrile sequelae, post-acute infectious syndromes, and the narratives of sufferers unable to fully recover from febrile infectious diseases. Taken together, these approaches invite a renewed reckoning with fever as both a biological phenomenon and a social and cultural object.