EasonYD88/Compuchem_selflearn_resources
A structured, community-driven learning hub for computational chemistry, covering foundations, methods, tools, practical workflows, and hands-on examples to help learners build a clear and systematic understanding of the field.
This resource provides a structured roadmap and learning materials for computational chemistry. It takes you from foundational concepts in math, programming, and chemistry/physics, through various subfields and practical software like AMBER or Gaussian. The output is a clear, systematic understanding of computational chemistry, enabling you to apply it in research or industry. It's designed for students, researchers, or professionals looking to enter or deepen their expertise in this field.
Use this if you are new to computational chemistry and need a clear, comprehensive, and structured learning path to build foundational knowledge and practical skills.
Not ideal if you are an experienced computational chemist primarily looking for highly specialized, advanced research tools or niche software documentation.
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License
MIT
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Last pushed
Jan 05, 2026
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