CDS Rapid Analytics and Model Prototyping + Training Sprints

Objective: solving real problems and hands-on data science training

The Paris-Saclay Center for Data Science has started a new series of data science training sessions. The objective of the events is to give novice data scientists (and domain scientist interested in data science) hands-on experience on real problems. The participants will learn about practical issues such as casting and formalizing a problem into a model, data normalization, diagnosing and debugging a model, model and algorithm selection, parameter tuning, and postprocessing. Another important objective of the training is to introduce a wide range of applications in various domains (astrophysics, brain imaging, economics, etc.).

Format and content

Based on the experience of our first two bootcamps,  we have decided to alter the format slightly. We will continue running problem-solving days that we re-baptized RAMPs (Rapid Analysis and Model Prototyping). The next event will take place on April 10. We will classify variable stars based on their light curves, brought to you by Marc Moniez (LAL), Gilles Faÿ (CentraleSupelec), and your regular coaches (Alex, Akin, Loic, Djalel, and Balazs). Please sign up at

before March 26.

The RAMP will be preceded by two three-hour Training Sprints (TSs) on April 7 for those who would like hands-on courses on the concepts and tools to be used in the RAMPs. In the first we we will teach you some basic notions about model complexity and learning curves and then show you how to use some tools to optimize your single models. Please sign up at

before March 26. In the second, we will teach you how to extract meaningful features from functional data (light curves) that you will be able to pass to the classifier. Please sign up at

before March 26.

The room capacity limits the number of participants to 40 in all these events, FCFS.

If you haven’t filled the form (that is, this is the first time you see this announcement), please fill it at

before signing up to any of the events.

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