## Program

Pre-school Program (6 - 9 August, 2019)

## Tuesday, August 6

9:30 Welcome

9:45 Programming / Math skills evaluation

10:00 Interactive Lecture - Introduction to Matlab: Data as Vectors, Indexing, Plotting, etc. (Christian Machens)

11:00 Coffee Break

11:30 Interactive Lecture - Introduction to Matlab: Data as Vectors, Indexing, Plotting, etc. (Christian Machens)

12:30 Practical Exercises

13:30 Lunch

15:00 Interactive Lecture - Matrices as Operators (Christian Machens)

16:00 Practical Exercises

17:00 Interactive Lecture - Matrix Decompositions: SVD, Eigenvalues and Eigenvectors, Principal Component Analysis, etc. (Christian Machens)

18:00 Practical Exercises

19.30 Dinner

## Wednesday, August 7

9:30 Interactive Lecture - Introduction to Calculus: Derivatives, Integrals, Minima / Maxima of Functions, Multivariate Calculus and Gradient Descent (Allan Mancoo)

10:30 Practical Exercises

11:00 Coffee Break

11:30 Interactive Lecture - Introduction to Calculus: Derivatives, Integrals, Minima / Maxima of Functions, Multivariate Calculus and Gradient Descent (Allan Mancoo)

12:30 Practical exercises

13:30 Lunch

15:00 Interactive Lecture - Differential Equations: Integrate-and-Fire neuron, Euler method(Sander Keemink)

16:00 Practical Exercises

17:00 Interactive Lecture - Differential Equations: Phase Space Plots, Fixed point attractors, Limit cycles (Sander Keemink)

18:00 Practical Exercises

19:30 Dinner

## Thursday, August 8

9:30 Interactive Lecture - Convolutions, Fourier Analysis I (Gonçalo Guiomar)

10:30 Practical Exercises

11:00 Coffee Break

11:30 Interactive Lecture - Convolutions, Fourier Analysis II (Gonçalo Guiomar)

Convolutions, Fourier Analysis II

12:30 Practical Exercises

13:30 Lunch

15:00 Interactive Lecture - Statistics I: Probabilities and Bayes (Margarida Sousa)

16:00 Practical Exercises

17:00 Interactive Lecture - Statistics II: Elementary Distributions (Margarida Sousa)

18:00 Practical Exercises

19:30 Dinner

## Friday, August 9

9:30 Interactive Lecture - Introduction to Supervised Learning: Regression etc. (Adrian Jouary)

10:30 Practical Exercises

11:00 Coffee Break

11:30 Interactive Lecture - Introduction to Supervised Learning: Regression etc. (Adrian Jouary)

12:30 Practical Exercises

13:30 Lunch

15:00 Interactive Lecture - Introduction to Unsupervised Learning: Clustering etc.(Sander Keemink)

16:00 Practical Exercises

17:00 Wrap-up

20:00 Dinner