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
- 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.
- 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.
- Byte Sized Chemistry – A blog about digital chemistry and student life
- The Valence Kjell – A blog about computational chemistry, cheminformatics and machine learning
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.