Courses from 1000+ universities
Buried in Coursera’s 300-page prospectus: two failed merger attempts, competing bidders, a rogue shareholder, and a combined market cap that shrank from $3.8 billion to $1.7 billion.
600 Free Google Certifications
Academic Writing Made Easy
Mechanics of Materials I: Fundamentals of Stress & Strain and Axial Loading
Digital Marketing
Organize and share your learning with Class Central Lists.
View our Lists Showcase
Explore practical applications of complex integration theorems through challenging examples, enhancing your understanding of advanced mathematical concepts.
Explore the residue theorem and learn to compute complex contour integrals around singular points, culminating in the integral of f(z)=1/z.
Explore contour integration in complex analysis, covering theorems, continuous deformation, and integration around singularities for a deeper understanding of complex functions.
Explore how analytic complex functions' real and imaginary parts solve Laplace's equation, introducing harmonic functions in this in-depth mathematical analysis.
Explore analytic complex functions and learn to test for analyticity using Cauchy-Riemann conditions in this comprehensive mathematical exploration.
Explore complex logarithms and exponentials to compute fractional powers of complex numbers, including nth roots of unity and special cases like the square root of i.
Explore complex functions including monomials, exponentials, and trigonometric functions. Learn about Taylor series and important identities in complex analysis.
Explore chaos and uncertainty propagation in dynamical systems through numerical integration. Learn efficient vectorization techniques in Python and MATLAB for faster computations.
Learn to implement a 4th-order Runge-Kutta integrator in Python and Matlab, and apply it to simulate the chaotic Lorenz 1963 system. Gain practical coding skills for numerical integration.
Comprehensive introduction to Runge-Kutta schemes for numerical integration of differential equations, covering RK2 and RK4 methods with intuitive explanations and visual representations.
Explore Forward and Backward Euler integration methods for ODEs using Python and Matlab. Compare stability, error, and implementation on a spring-mass-damper system with analytic solutions.
Explore Forward and Backward Euler integration methods for ODEs, including derivations, error sources, and stability analysis. Gain insights into numerical integration techniques for solving differential equations.
Explore numerical integration of ODEs to analyze nonlinear systems and generate trajectories. Learn techniques for solving complex dynamics where analytic methods fall short.
Learn to solve forced linear differential equations using the powerful method of variation of parameters, replacing unknown coefficients with time-dependent functions based on external forcing.
Learn to solve linear differential equations with external forcing using the method of undetermined coefficients. Understand homogeneous solutions, particular solutions, and how to combine them for a complete solution.
Get personalized course recommendations, track subjects and courses with reminders, and more.