Through short lectures, in-class activities, and problem sets, students learn and use methods in data science to complete projects focused on (i) descriptive and predictive analyses of chemical processes and (ii) Quantitative Structure Property Relationships (QSPR). Topics covered may include six sigma, Statistical Process Control (SPC) & Statistical Quality Control (SQC); time-series analysis; data preprocessing; dimensionality reduction; supervised, reinforcement, and unsupervised learning; decision tree & clustering methods; univariate and multivariate regression; and visualization.
Data is everywhere, but it's always a challenge to find quality data sets relevant for chemical engineers. Get started here.
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Data science revolutionizes how chemical engineers and other STEM professionals solve problems and discover new materials & methods.
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Looking for data science positions that will allow you to use your domain expertise in chemical engineering or related skills?
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Make your work re-usable and reproducible using best practices for data management & storage, statistics & analyses, and code standards & control.
Improve NowWhere can you apply your data science skills in ChE-relevant competitions?
You can always participate in competitions, where you can test your data-science problem-solving skills while utilizing methods you know -- or learning new algorithms that are more suitable. The trick is to find the right opportunities for chemical engineers.
And don't be afraid to try your hand at closed competitions for which data are still available. Sure, you won't be eligible for prizes, but you'll know exactly where you stand overall and can learn new techniques to solve problems.
With that in mind, click below to find 10+ multi-year competitions.
ChE Data Science CompetitionsChE141 is a required course in Chemical Engineering's computational track, one of five areas of focus in the ChE BS degree program.
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ChE141 (partially) fulfills the "Applications of Data Science" requirement for a (major) minor in Information & Data Sciences.
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