Solving Initial Value Problems in Chemical Engineering with MATLAB — PickAClass
⏱ 2h 42m 📚 27 lessons 🎧 Audio version

Solving Initial Value Problems in Chemical Engineering with MATLAB

Learn to implement the Quasi-Steady-State Approximation and numerical methods in MATLAB to model complex chemical reaction kinetics.

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About this course

In chemical engineering, modeling rapid reaction rates and complex kinetics often leads to stiff differential equations that are difficult to solve with standard numerical methods. This written course guides you through the foundational concepts of Initial Value Problems (IVPs) and how to solve them efficiently. You will learn how to simplify these mathematical models using approximation techniques and translate them into clean, functional MATLAB scripts. What you'll learn: Understand the core principles of Initial Value Problems and stiff differential equations in chemical systems; Apply the Quasi-Steady-State Approximation (QSSA) to simplify complex kinetic models; Write and structure MATLAB scripts to solve systems of ordinary differential equations; Analyze chemical engineering scenarios to determine when to use stiff versus non-stiff numerical solvers; Debug and optimize your numerical code for stability and accuracy. This course begins with essential mathematical and chemical engineering definitions before moving step-by-step through code construction and practical modeling scenarios. It is designed for undergraduate students, researchers, and beginning engineers who want to build a solid foundation in numerical methods using MATLAB without needing advanced prior programming experience. Start mastering chemical kinetics modeling today.

What you'll get

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  • Short & focused
    2h 42m of practical content

Certificate of completion

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Solving Initial Value Problems in Chemical Engineering with MATLAB
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A/B test design
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Solving Initial Value Problems in Chemical Engineering with MATLAB
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Performance detail
Coursework summary
Lessons completed 14 / 14
Practice questions 26 / 28
Assignments submitted 4 (avg 4.5 / 5)
Capstone project Reviewed — 4.6 / 5
Total practice 6.2 hrs
Performance benchmark
Cohort rank Top 12% of 1,625
Time to completion 11 days (median: 22)
Mastery score 91 / 100
Practice-question score 94%
Skill verification Verified Skill Path
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Issued under the academic standards of PickAClass. Skill levels reflect assessed performance against the course's competency rubric. This is an original credential of this platform.

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