Computational Chemistry Fundamentals
You don't need a CS degree to model molecules. This course teaches the intuition behind computational methods — DFT, MD, force fields — and gets you running simulations in Python by week two.
About this course
Computational chemistry is not a niche skill anymore. Whether you're in academia or industry, the ability to run and interpret molecular simulations is increasingly expected — and increasingly accessible.
This course teaches the 20% of computational methods that cover 80% of real research scenarios. Theory is taught in service of practice — every concept is immediately applied in Python, so you leave with working code, not just notes.
What you'll cover
- 1Quantum chemistry basics: Schrödinger, HF, and DFT
- 2Force fields and molecular dynamics
- 3Python for chemical data: RDKit, ASE, and pymatgen
- 4Setting up and running DFT jobs (VASP / Gaussian overview)
- 5Reading and interpreting simulation output
Who this is for
Audience
Chemists, materials scientists, and engineers new to simulation
Prerequisites
Undergraduate chemistry background. Basic Python helpful but not required.
Your instructor
Kevin Braza
PhD Candidate, UC Davis · CBRN AI Safety Scientist
Chemical engineering PhD candidate, Quantic MBA, former boarding school faculty, and CBRN AI safety scientist at Reinforce Labs. Previously UCSB B.S. Chemistry, Harvard/Amgen, and IB + AP classroom instructor. Teaches at the intersection of chemistry, AI, and systems thinking.
Frequently asked
Do I need to know Python?
Helpful but not required. The course teaches what you need as you need it — the chemistry knowledge is the real prerequisite.
What software do I need?
Everything used is free and open source. Setup instructions are included in Module 1.
Is this relevant for a PhD application?
Yes. Having computational chemistry experience — even beginner-level — is a differentiator in PhD applications in chemistry, materials science, and chemical engineering.
$997
One-time · Lifetime access
Includes
- 5 modules + hands-on Python labs
- Code templates and starter notebooks
- Lifetime access
- Certificate of completion