This series of modules introduce key concepts in data science in the context of application in materials science and engineering. The end to end modules include:
- A recorded lecture that introduces each topic and provides background material,
- A hands-on tutorial with step-by-step instructions to perform interactive online activities and run interactive code,
- A homework assignment designed to help users explore the concepts using online models and simulations and adopt the code to problems of their interest.
The modules are self-contained and modular, they are designed for easy incorporation into existing courses or for those interested in self-study.
All interactive computing is performed using cloud computing in nanoHUB, there is no need to download or install any software. All resources are open and free.
Knowledge and Skills
- Data handling
- Predictive modeling
- Decision making
- Uncertainty quantification – See Module 6
- Active learning for design of experiments – See Module 7
The interactive computing is performed using python through Jupyter notebooks. Basic programing skills are required. An introductory tutorial on Jupyter, python and plotting is available at: https://nanohub.org/resources/33266
Cite this work
Researchers should cite this work as follows:
Hands-on Learning Modules on Data Science and Machine Learning in Engineering
This resource belongs to the Hands-on Learning Modules on Data Science and Machine Learning in Engineering group.