Numerical Methods in Chemical Engineering with Python

Chemical engineers constantly face complex design, reactor, and transport problems that cannot be solved with paper and pencil alone. Translating physical principles into robust computational models is an essential skill in modern industry and research. This text-based course guides you from core mathematical concepts to practical computational implementation, giving you the tools to simulate and analyze real engineering systems. You will learn to formulate, solve, and analyze engineering models step-by-step. What you'll learn: Understand foundational numerical concepts including error analysis and convergence; Solve systems of linear and non-linear algebraic equations representing chemical processes; Formulate and solve ordinary differential equations for chemical reactors and transport phenomena; Apply modern Python libraries like NumPy and SciPy to automate engineering calculations; Implement basic optimization techniques to find ideal operating parameters. This course begins with essential mathematical terminology and foundational concepts before moving on to practical modeling scenarios. You will read clear explanations, study structured code snippets, and work through guided engineering problems to build your confidence. This course is designed for beginner chemical engineering students and practicing engineers who want to learn numerical methods using modern Python tools. No prior programming experience is required, though a basic understanding of calculus and chemistry is helpful. Start building your computational engineering toolkit today.