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 Gaussian Mixture Models, Denoising, Data Classification, and Spike Sorting using Principal Component Analysis.
Covers exercises on genome-scale metabolic models, including FBA and TFA analysis, as well as modeling kinetics.
Introduces a programming course for engineers, emphasizing the importance of mastering multiple languages for future projects.
Explores numerical integration methods and their application in solving differential equations and simulating physical systems.
Explores parametric spectrum estimation methods, including line and smooth spectra, and delves into heart rate variability analysis.
