Big Data for Chemistry Course
Master big data in chemistry: develop scalable pipelines, create effective data models, calculate vital molecular metrics, and use machine learning on simulation data to speed up materials discovery and support key technology choices.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Big Data for Chemistry Course teaches how to convert large molecular simulation results into dependable, searchable knowledge. Learn to build scalable data intake systems, process various formats, create chemical features, and develop strong analytical models. Gain hands-on experience with validation, quality assurance, and machine learning processes to rank materials, measure uncertainty, and speed up data-guided discoveries.
Elevify advantages
Develop skills
- Design big data systems for molecular simulations, quick and large-scale.
- Create strong ingestion pipelines for XYZ/PDB logs with Spark, Dask, and Airflow.
- Develop chemical features such as Henry constants, diffusion, and selectivity measures.
- Use ML models to forecast gas uptake and rank materials confidently.
- Set up quality checks, monitoring, and cost management for high-volume chemistry processes.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workloadWhat our students say
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