Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.
Explores fluid-solid coupling dynamics, stability analysis, and system response to external disturbances using MATLAB simulations.
Covers eigenvalues, eigenfunctions, Hermitian operators, and the measurement of observables in quantum chemistry.
Covers the basics of Python programming, focusing on flow control structures, interactive mode, script mode, and variables.
Explores turbulence characteristics, simulation methods, and modeling challenges, providing guidelines for choosing and validating turbulence models.
Explores neurophysiological data analysis, covering AP identification, firing rates, subthreshold activity, FFT spectral analysis, and event-triggered analysis using MATLAB.
