Data analysis is a stransversal topic across algorithmics, statistics, and optimization. It relies on high-level languages such as Python or R for data handling and processing. This introductory course will consider both theoretical and practical aspects of data analysis.
References:
- Hastie, Tibshirani, Friedman: The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd ed.). Springer, 2017.
- Scott and Stain: Multi-dimensional Density Estimation. In Handbook of Statistics, Volume 23 (Data Mining and Computational Statistics), 2004.
- Teaching coordinator: Berkemer Sarah
- Teaching coordinator: Butler Tara
- Teaching coordinator: Chennoufi Sara
- Teaching coordinator: Ehrhardt Adrien
- Teaching coordinator: Krejca Martin
- Teaching coordinator: Oudot Steve
- Teaching coordinator: Pogudin Gleb
- Teaching coordinator: Sureshkumar Anandhu
- Teaching coordinator: Tomchuk Bogdan
- Teaching coordinator: Tsigaridas Elias