CHBE 413

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Credit: 4 hours.

Introduction to machine learning and deep learning in the context of chemical sciences. Students gain hands-on experience through in-class exercises and homework using real data sets from chemistry, chemical engineering, biomolecular engineering, and material science. Unique processing and featurization techniques relevant to the chemistry sector are taught. Guest lectures by chemical data scientists from industry and academia offer insight into practical applications and potential career paths. The course concludes with a team-based project on cutting-edge machine learning.

Same as CHEM 452. 4 undergraduate hours. No graduate credit. Prerequisite: MATH 225, MATH 227, MATH 257, or MATH 415. Restricted to Junior or Senior standing. Knowledge of essential programming constructs (e.g. functions, loops, conditional statements) in the context of a programming language (e.g. C/C++, Fortran, Java) is required. Basic proficiency with the Python programming language is strongly recommended.

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