Numerical Methods for Chemical Engineering

Chemical engineering problems often involve complex mathematical models that require computational solutions. Develop the skills to tackle these challenges by mastering fundamental numerical methods. This course will guide you through the principles and practical applications of numerical techniques, empowering you to accurately model and solve engineering scenarios using modern computational tools. What you'll learn: - Understand the core concepts of numerical analysis and their relevance in engineering. - Implement iterative methods for solving non-linear equations and systems of equations. - Apply numerical integration and differentiation techniques to chemical process data. - Solve ordinary differential equations common in reaction kinetics and transport phenomena. - Utilize Python with libraries like NumPy and SciPy for efficient numerical computation. - Evaluate the accuracy and stability of numerical solutions through error analysis. The course begins with an introduction to numerical computing fundamentals, progressing through various methods for solving algebraic equations, calculus problems, and differential equations. Each topic includes practical examples and exercises designed to reinforce understanding. This course is designed for beginners in chemical engineering or related fields who want to learn how to apply numerical methods. No prior experience with numerical methods or Python programming is required. Start building your essential toolkit for computational chemical engineering today.