Explore pre-class lectures and slides for Scientific Computing 1 (Physics 280) at the University of Indianapolis. Delve into topics such as the Euler Method, Heun Method, Taylor Series, Monte Carlo simulations, matrix methods in optics, power laws, numerical integration, root finding, coupled oscillators, and an introduction to supervised machine learning with the Perceptron. Learn to apply Python, Numpy, and Jupyter Notebooks to solve complex scientific computing problems. Gain hands-on experience with Fourier transforms, curve fitting, and eigenvector applications in stochastic matrices and coupled oscillators. Master essential tools and techniques for computational physics and scientific analysis over the course of 6 hours of comprehensive content.