Hi everyone, I’m about to start a MS in CE (controls/robotics focus). I have the possibility to (unnecessarily) add a course called “Mathematics in Machine Learning”, 8 ECTS, in my second semester, making it go from 24 to 32 ECTS. The temptation arises from the fact that proving that I own strong maths foundations in ML could result in good ML research positions and salaries. However, I’ll also have to do compulsive courses like Convex Optimization and general ML, so I’d get a good basis anyway.

My question is: is the “extra” work worth it, or won’t companies care at all?

The course programme is the following:

• Mathematical representations of data: spaces (including Hilbert spaces), metrics, distances, dissimilarities and kernels. Geometry of very high dimensional spaces and the curse of dimensionality.
• Learning theory, PAC, Rademacher and VC dimension. Trade-off Bias vs Model Variance and Model Complexity.
• Cross validation, bootstrap and applications.
• Linear algebra-based methods: Principal Component Analysis, Linear Discriminant Analysis, Independent Component Analysis and Stochastic projections (Johnson – Lindenstrauss Transform).
• Linear Models (regression, ANOVA, DOE).
• Generalized linear models (categorical data, logistic and multinomial regression).
• Model and feature selection, hyperparameter tuning (e.g. lasso, AIC, BIC, ridge).
• Bayesian networks (basic concepts, exact and MCMC-based computations).