Tuesday, Aug 2
   9:30 Welcome
   9:45  Programming / Math skills evaluation
10:00  Interactive Lecture (Christian Machens)
Introduction to Matlab: Data as Vectors, Indexing, Plotting, etc.

11:00  Coffee Break

11:30  Interactive Lecture (Christian    Machens)
Introduction to Matlab: Data as Matrices, Indexing, Plotting, etc.
12:30 Practical Exercises

13:30 Lunch

15:00 Interactive Lecture (Christian Machens)
Matrices as Operators: Inner products, projections, Coordinate transforms, different types of matrices etc.
16:00 Practical Exercises

17:00 Interactive Lecture (Christian Machens)
Matrix Decompositions: SVD, Eigenvalues and Eigenvectors, Principal Component Analysis, etc.
18:00 Practical Exercises

19.30 Dinner


Wednesday, Aug 3
   9:30 Interactive Lecture (Paulo Aguiar)
Matlab programming: Scripts and Functions, Flow Control (loops, conditions),
Handling of Variables etc., Getting Help, Advanced Concepts
10:30 Practical Exercises

11:00 Coffee Break

11:30  Interactive Lecture (Pedro Goncalves)
Introduction to Calculus: Derivatives, Integrals, Minima / Maxima of Functions,
Multivariate Calculus and Gradient Descent
12.30  Practical Exercises

13:30 Lunch

15:00 Interactive Lecture (Pedro Goncalves)
Differential Equations: Integrate-and-Fire neuron, Euler method
16:00 Practical Exercises

17:00 Interactive Lecture (Pedro Goncalves)
Differential Equations: Phase Space Plots, Fixed point attractors, Limit cycles
18:00 Practical Exercises

19:30 Dinner


Thursday, Aug 4
   9:30 Interactive Lecture (Paulo Aguiar)
Convolutions, Fourier Analysis I
10:30 Practical Exercises

11:00 Coffee Break

11:30   Interactive Lecture (Paulo Aguiar)
Convolutions, Fourier Analysis II
12:30 Practical Exercises

13:30 Lunch

15:00 Interactive Lecture (Dmitry Kobak)
Statistics I: Probabilities and Bayes
16:00 Practical Exercises

17:00 Interactive Lecture (Dmitry Kobak)
Statistics II: Elementary Distributions
18:00 Practical Exercises

19:30 Dinner


Friday, Aug 5
  9:30 Interactive Lecture (Christian Machens)
Introduction to Supervised Learning: Regression etc.
10:30 Practical Exercises

11:00 Coffee Break

11:30  Interactive Lecture (Dmitry Kobak)
Introduction to Unsupervised Learning: Clustering etc.
12:30  Practical Exercises

13:30 Lunch

15:00 Interactive Lecture (Dmitry Kobak / Christian Machens)
Introduction to Unsupervised Learning: PCA / SVD revisited
16:00 Practical Exercises

17:00 Wrap-up

20:00 Dinner Out in Lisbon