Short Trainings & Workshops

The first part of the workshop will introduce the different types of uncertainty, like aleatoric and epistemic ones, and define the typical uncertainty metrics. The second part will detail several techniques to define and estimate uncertainty in machine learning projects: Bootstrapping, Ensemble methods, Bayesian approaches and Quantile regression. The third part of the workshop is dedicated to a more recent and promissing technique: Conformal Prediction. The last part is a hands-on session in python to experiment with these diffent techniques, with simple datasets.

In this course we will guide the audience through the challenges of framing a data science project that can be tackled using data science techniques. Share previous experience from public and private sector. Provide hands-on tutorial on how to fill a data science canvas.

This introduction aims to position the topic of natural language processing within the wider scope of artificial intelligence applications. The foundations and state of the art of the discipline will be introduced, together with its core tasks and applications. Concrete examples of natural language processing techniques powering Swiss organizations will be presented together with final remarks concerning limitations and perspectives of the field.

This course is a high-level introduction to Generative AI techniques, with the focus on recent developments of large language models (LLMs), to demystify these techniques and discuss practical business applications.Techniques involving images, sound and tabular data, as well as multi-modal systems will be discussed.The course will also introduce basic concepts and best practices in prompt engineering.The last part of this course is dedicated to a hands-on session where participants will work with LLMs on specific tasks (summarization, generation, translation...).