This video describes how you can use MRST to construct Cartesian and rectilinear grids for rectangular and non-rectangular domains and show how you can populate your grid with petrophysical properties.

In this livestream, Ed Marquez and Connell D’Souza walk you through the fundamentals of using Simulink.

Table arrays store column-oriented or tabular data, such as columns from a text file or spreadsheet. Tables store each piece of column-oriented data in a variable. Table variables can have different data types and sizes as long as all variables have the same number of rows. In this session, Heather uses examples to outline the syntax and functions for working with tables in MATLAB.

In this master class, you will learn how data analytics can turn large volumes of complex data into actionable information and improve design and decision-making processes.

Learn how you can use MATLAB and Python integration to improve the compatibility and usability of your code.

This intuitive introduction shows the mathematics behind the Z-transform and compares it to its similar cousin, the discrete-time Fourier transform. Mathematically, the Z-transform is straightforward—it’s just a bunch of multiplications and additions, and you’ll learn how to solve an equation for a few different signals. However, understanding how to solve a Z-transform equation isn’t as important as understanding why the math is the way it is. Therefore, the majority of this tech talk discusses what you are actually doing when you take the Z-transform of a signal.

The video lecture series by Gilbert Strang on Linear Algebra is one of the most widely recognized resources for learning the subject, based on the course taught at the Massachusetts Institute of Technology. With a clear and intuitive approach, Strang emphasizes conceptual understanding through geometric interpretations and practical applications, going beyond mere algebraic manipulation. The videos cover fundamental topics such as linear systems, matrices, determinants, vector spaces, eigenvalues and eigenvectors, and matrix factorizations (such as LU and SVD), consistently connecting theory with applications in data science, engineering, and physics. The engaging and progressive teaching style makes the series suitable for both beginners and advanced students seeking to strengthen their foundations. It is an excellent resource for anyone aiming to build a solid and applied understanding of Linear Algebra.

Computational Fluid Dynamics (CFD) is a system analysis involving the transport of properties through computational simulations, such as fluids, heat, etc. This course will cover CFD concepts using the OpenFOAM tool, an acronym for “Opensource Field Operation And Manipulation,” which is a C++-based program for solving Continuum Mechanics problems. OpenFOAM includes all the necessary routines for solving CFD problems, from pre-processing (creation of meshes, for example) to post-processing (for acquiring results and an interface for visualizing fields in a 3D domain).

Applied Digital Signal Processing at Drexel University: In this video are introduced the z-Domain and the z-Transform, which provide key insights for DSP and an intuitive approach to filter design.