You are welcome to contribute to this project! See CONTRIBUTING.md for details.
Table of content:
- Foundational Knowledge
- Core Topics in Digital Chemistry
- Courses
- Tutorials
- Blogs and Articles
- Communities and Resources
- Related Awesome Lists
- Neural Networks: Zero to Hero – A Tutorial on the basics of Neural Networks and NLP
- The Turing Way – Resources on Data Managment/Reproducible Science
- Introduction to version control for scientists
- Scientific Computing for Chemists
- MolSSI Education: Python Scripting CMS
- Deep Learning for Chemistry 101
- AI4Chemistry course - The Artificial Intelligence (AI) for Chemistry taught in Spring 2023 at EPFL (CH-457). It is a course with a lot of hands-on exercises. Experience in Python programming and machine learning (ML) will help you to get up to speed quickly.
- Practical Programming – This course offers a thorough introduction to programming for chemists and chemical engineers using Python, covering fundamental concepts and tools relevant to chemical tasks, from Git to the RDKit. The exercises are freely accessible.
- Machine Learning for Materials – An introduction to statistical research tools for materials theory and simulation at the Department of Materials at ICL.
- VolkamerLab Talktorials on CADD – "Talktorials" (portmanteau for talk and tutorial) address many topics central to computer-aided drug design. Topics range from cheminformatics, online queries to structural biology.
- Practical Cheminformatic Tutorials by Patrick Walters – Jupyter notebooks and Google colab notebooks for learning Cheminformatics. From fundamentals of concepts in cheminformatics over clustering, SAR analysis, machine learning and active learning: This course covers everything!
- Transformers for Chemistry and Materials Science – A collection of the LlamaLab's tutorials on transformers in chemistry and materials science, adapted from blogposts from Kevin M. Jablonka's Blog.
- Official code tutorial for ACS In Focus (2024) - Neural Networks for Chemists – a collection of first-step knowledge and tools to begin harnessing the power of neural networks in your own work.
- The Valence Kjell – A blog about computational chemistry, cheminformatics and machine learning
- Practical Cheminformatics (here since April 2025) – A blog by Pat Walters about many topics in cheminformatics, among others, generative models, LLMs and machine learning in drug discovery.
- Byte Sized Chemistry – A blog about digital chemistry, data visualization and student life
Do you want a Digital Chemistry blog to be featured? Let us know by submitting a pull request!
- OpenBioML - OpenBioML is a decentralized, collaborative research community founded on the belief that open source machine learning and open science can accelerate biotechnology.
- LeMaterial – LeMaterial is an open-source collaborative project designed to simplify and accelerate materials research for scientists and ML practionners. By joining the slack and monthly community meetings, you are able to contribute to working groups for large language models, generative models and benchmarks in materials science.