Chemical
Process modelling, optimisation and data-driven methods for chemical engineers.
Beginner
Start here. No background needed beyond school maths.
Advanced
Once the basics are comfortable.
NPTEL: Machine Learning for Core Engineering Disciplines
An IISc Bangalore course that teaches machine learning through examples from chemical, mechanical and materials engineering, from regression to neural networks, with Python practice.
NPTEL / IISc Bangalore
Optimization Bootcamp
The optimisation methods behind both machine learning and process design: convexity, gradient descent, constrained optimisation and duality, explained step by step.
Steve Brunton (University of Washington)
APMonitor: Dynamic Optimization
BYU's free course on modelling, estimation and model predictive control of chemical and energy processes, with Python.
John Hedengren, Brigham Young University
DeepChem Tutorials
Open-source tutorials on deep learning for chemistry, molecules and materials: featurisation, property prediction and generative models.
DeepChem
NPTEL: Data Science for Engineers
Taught by IIT Madras chemical engineering faculty: the linear algebra, statistics and optimisation behind data science, with R examples.
NPTEL / IIT Madras