Data Science for Chemical Systems
9 units (1-2-6) |
Prerequisites: ChE 15, ACM/IDS 104.
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; SPC & SQC; time-series analysis; data preprocessing; dimensionality reduction; supervised, reinforcement, and unsupervised learning; decision tree & clustering methods; univariate and multivariate regression; and visualization. Python is the programming language of instruction.
The online version of the Caltech Catalog is provided as a convenience; however, the printed version is the only
authoritative source of information about course offerings, option requirements, graduation requirements,
and other important topics.