This repository is used for for lecture notes for ChBE 4745/6745 - Data Analytics for Chemical Engineers. The course is organized by modules. Under each module, you will find a Jupyter notebook for specific topics. The modules are:

Numerical Methods - basics of programming, linear algebra, and optimization.

Regression - introduction to non-parametric regression models, hyperparameter optimization, and regression methods for high-dimensional data.

Classification - formalism of classification problems, generalized linear models, and other classification techniques.

Data Management - overview of strategies for data organization and introduction to APIs and online data access.

Exploratory Data Analysis - unsupervised learning techniques including clustering, dimensional reduction, and generative models.

Feature Engineering - basic strategies for selecting features, creating features from categorical data and time series analysis.

All course logistics and assignments for the Georgia Tech "Data Analytics for Chemical Engineers Course" will be handled through the course Canvas page.