Data-Driven Reaction Engineering Using Machine Learning – Training Services

Data-Driven Reaction Engineering Using Machine Learning – Training Services focuses on integrating machine learning (ML) techniques into reaction engineering for predictive modeling, optimization, and analysis of complex chemical systems. Participants learn to preprocess experimental reaction data, apply supervised and unsupervised ML algorithms, and develop surrogate models for kinetic parameter estimation and reactor performance prediction. The training also covers techniques such as regression, classification, clustering, dimensionality reduction, and model validation specifically tailored to reaction engineering challenges. Emphasis is placed on using Python-based tools and real-world datasets to enhance decision-making in reactor design, control, and scale-up.