The course is divided into two modules, centered around a practical problem chosen by the professor:
- Module 1: Data Organization with dbt (30 hours)
- Module 2: Advanced Data Analysis and Modeling (30 hours)
- Hastie, Trevor, Robert Tibshirani, and Jerome Friedman. The elements of statistical learning. Springer New York, 2009.
- Bishop, Christopher M. Pattern recognition and machine learning. springer, 2006.
- Murphy, K. P.. Machine Learning, A Probabilistic Perspective. MIT Press, 2012
- Duda, R. O., Hart, P. E. and Stork, D. G. Pattern Classification (2nd Edition). Wiley-Interscience, 2000.
- Yu, Dong, and Li Deng. Automatic speech recognition: A deep learning approach. Springer, 2014.
- Jannach, Dietmar, et al. Recommender systems: an introduction. Cambridge University Press, 2010.
- Ekstrand, Michael D., John T. Riedl, and Joseph A. Konstan. "Collaborative filtering recommender systems." Foundations and Trends® in Human – Computer Interaction 4.2 (2011): 81-173. (http://www.nowpublishers.com/article/Details/HCI-009)
- Goodfellow, Ian, Yoshua Bengio, and Aaron Courville. Deep learning. MIT press, 2016. (http://www.deeplearningbook.org/)