Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.
Explores parametric spectrum estimation methods, including line and smooth spectra, and delves into heart rate variability analysis.
Covers Gaussian Mixture Models, Denoising, Data Classification, and Spike Sorting using Principal Component Analysis.
Explores total scattering and PDF analysis in materials science, covering in-situ synthesis, data analysis techniques, and applications in host-guest systems.
Introduces a programming course for engineers, emphasizing the importance of mastering multiple languages for future projects.
Covers eigenvalues, eigenfunctions, Hermitian operators, and the measurement of observables in quantum chemistry.
Covers topics in Quantum Chemistry, including history, tools, color & draw techniques, shapes, and mathematical conversions.
Explores neurophysiological data analysis, covering AP identification, firing rates, subthreshold activity, FFT spectral analysis, and event-triggered analysis using MATLAB.
Explores numerical integration methods and their application in solving differential equations and simulating physical systems.
Covers macroeconomic models incorporating financial markets, analyzing financial decisions, macroeconomic events, and policy responses.
