Covers exercises on genome-scale metabolic models, including FBA and TFA analysis, as well as modeling kinetics.
Covers Gaussian Mixture Models, Denoising, Data Classification, and Spike Sorting using Principal Component Analysis.
Covers vectorisation, functions, and flow control in Matlab, emphasizing the importance of avoiding global variables and providing examples of simple plots and debugging techniques.
Covers macroeconomic models incorporating financial markets, analyzing financial decisions, macroeconomic events, and policy responses.
Explores numerical integration methods and their application in solving differential equations and simulating physical systems.
Covers the training process of a neural network, including feedforward, cost function, gradient checking, and visualization of hidden layers.
Explores parametric spectrum estimation methods, including line and smooth spectra, and delves into heart rate variability analysis.
Explores neurophysiological data analysis, covering AP identification, firing rates, subthreshold activity, FFT spectral analysis, and event-triggered analysis using MATLAB.
Explores nonlinear truss system analysis, covering force-displacement responses, event-to-event principles, and solution algorithms.
