Students will put their basic machine learning and data analysis knowledge to test for solving practical data science problems in scientific or industrial applications. Typically, we will treat two/three concrete problems coming from scientific or industrial applications (e.g., brain imaging, astrophysics, biology/chemistry, ad placement, insurance pricing). We describe and formalize the motivating problem, discuss the possible solutions, choose one, and assist the students in solving the problem. We will provide data, advise students on their choice of tools, and set up a challenge environment where students can submit their solutions. Evaluation will be based on homework assignments and performance in the challenges.
Evaluation at the end of each data camp
- Teaching coordinator: Erwan Le Pennec