Applied Numerical Methods: Solve Engineering and Scientific Problems

When analytical mathematical formulas fail to solve complex real-world engineering and scientific problems, computer-driven numerical methods bridge the gap. This course offers a clear, structured path to understanding how algorithms approximate solutions to complex mathematical equations. You will transition from theoretical formulas to practical computational problem-solving, gaining the confidence to analyze and resolve engineering challenges programmatically. What you'll learn: - Understand the core concepts of numerical approximation, truncation errors, and round-off errors - Solve systems of linear and non-linear algebraic equations using iterative and direct methods - Apply interpolation and curve-fitting techniques to model complex experimental data sets - Implement numerical differentiation and integration methods to analyze rates of change and areas - Solve ordinary differential equations using standard numerical steps and modern error-control concepts The course begins with foundational concepts of error analysis and computer arithmetic, ensuring you understand how machines handle numbers. Next, you will progress through linear systems, root-finding, and integration, finishing with practical techniques for ordinary differential equations. This course is designed for engineering students, science majors, and entry-level developers with a basic background in calculus and introductory programming, requiring no advanced prior knowledge of numerical analysis. Start learning today and unlock the power of computational mathematics.