The best computational chemistry education in the world is free. Most people just do not know where to find it.
One rule before you start: pick one course that matches your level and complete it fully before moving to the next. Passive watching is not learning. Do the problems.
1. 𝑫𝒆𝒏𝒔𝒊𝒕𝒚 𝑭𝒖𝒏𝒄𝒕𝒊𝒐𝒏𝒂𝒍 𝑻𝒉𝒆𝒐𝒓𝒚 — É𝒄𝒐𝒍𝒆 𝑷𝒐𝒍𝒚𝒕𝒆𝒄𝒉𝒏𝒊𝒒𝒖𝒆, 𝑪𝒐𝒖𝒓𝒔𝒆𝒓𝒂
The only DFT course on Coursera. 4.8 stars. Taught by Lucia Reining and Francesco Sottile of the European Theoretical Spectroscopy Facility. HK theorems, KS equations, XC functionals, LDA, GGA, hybrid functionals, SCF. Three weeks, five to ten hours per week. Free to audit. 🔗 https://www.coursera.org/learn/density-functional-theory
2. 𝑺𝒕𝒂𝒕𝒊𝒔𝒕𝒊𝒄𝒂𝒍 𝑴𝒐𝒍𝒆𝒄𝒖𝒍𝒂𝒓 𝑻𝒉𝒆𝒓𝒎𝒐𝒅𝒚𝒏𝒂𝒎𝒊𝒄𝒔 — 𝑼𝒏𝒊𝒗𝒆𝒓𝒔𝒊𝒕𝒚 𝒐𝒇 𝑴𝒊𝒏𝒏𝒆𝒔𝒐𝒕𝒂, 𝑪𝒐𝒖𝒓𝒔𝒆𝒓𝒂
Statistical mechanics, partition functions, and thermodynamic properties from molecular principles. Essential foundation before any computational chemistry course. 🔗 https://lnkd.in/gyMNXNZb
3. 𝑮𝒆𝒏𝒆𝒓𝒂𝒍 𝑪𝒉𝒆𝒎𝒊𝒔𝒕𝒓𝒚: 𝑪𝒐𝒏𝒄𝒆𝒑𝒕 𝑫𝒆𝒗𝒆𝒍𝒐𝒑𝒎𝒆𝒏𝒕 — 𝑹𝒊𝒄𝒆 𝑼𝒏𝒊𝒗𝒆𝒓𝒔𝒊𝒕𝒚, 𝑪𝒐𝒖𝒓𝒔𝒆𝒓𝒂
Quantum mechanics of atoms, bonding, periodic trends, thermodynamics. Research-oriented, not a standard gen chem course. The right foundations before DFT. 🔗 https://www.coursera.org/learn/general-chemistry
4. 𝑰𝒏𝒕𝒓𝒐𝒅𝒖𝒄𝒕𝒊𝒐𝒏 𝒕𝒐 𝑪𝒉𝒆𝒎𝒊𝒔𝒕𝒓𝒚 — 𝑫𝒖𝒌𝒆 𝑼𝒏𝒊𝒗𝒆𝒓𝒔𝒊𝒕𝒚, 𝑪𝒐𝒖𝒓𝒔𝒆𝒓𝒂
Atomic structure, molecular geometry, quantum numbers, bonding. Start here if building from scratch. 🔗 https://www.coursera.org/learn/intro-chemistry
One rule before you start: pick one course that matches your level and complete it fully before moving to the next. Passive watching is not learning. Do the problems.
1. 𝑫𝒆𝒏𝒔𝒊𝒕𝒚 𝑭𝒖𝒏𝒄𝒕𝒊𝒐𝒏𝒂𝒍 𝑻𝒉𝒆𝒐𝒓𝒚 — É𝒄𝒐𝒍𝒆 𝑷𝒐𝒍𝒚𝒕𝒆𝒄𝒉𝒏𝒊𝒒𝒖𝒆, 𝑪𝒐𝒖𝒓𝒔𝒆𝒓𝒂
The only DFT course on Coursera. 4.8 stars. Taught by Lucia Reining and Francesco Sottile of the European Theoretical Spectroscopy Facility. HK theorems, KS equations, XC functionals, LDA, GGA, hybrid functionals, SCF. Three weeks, five to ten hours per week. Free to audit. 🔗 https://www.coursera.org/learn/density-functional-theory
2. 𝑺𝒕𝒂𝒕𝒊𝒔𝒕𝒊𝒄𝒂𝒍 𝑴𝒐𝒍𝒆𝒄𝒖𝒍𝒂𝒓 𝑻𝒉𝒆𝒓𝒎𝒐𝒅𝒚𝒏𝒂𝒎𝒊𝒄𝒔 — 𝑼𝒏𝒊𝒗𝒆𝒓𝒔𝒊𝒕𝒚 𝒐𝒇 𝑴𝒊𝒏𝒏𝒆𝒔𝒐𝒕𝒂, 𝑪𝒐𝒖𝒓𝒔𝒆𝒓𝒂
Statistical mechanics, partition functions, and thermodynamic properties from molecular principles. Essential foundation before any computational chemistry course. 🔗 https://lnkd.in/gyMNXNZb
3. 𝑮𝒆𝒏𝒆𝒓𝒂𝒍 𝑪𝒉𝒆𝒎𝒊𝒔𝒕𝒓𝒚: 𝑪𝒐𝒏𝒄𝒆𝒑𝒕 𝑫𝒆𝒗𝒆𝒍𝒐𝒑𝒎𝒆𝒏𝒕 — 𝑹𝒊𝒄𝒆 𝑼𝒏𝒊𝒗𝒆𝒓𝒔𝒊𝒕𝒚, 𝑪𝒐𝒖𝒓𝒔𝒆𝒓𝒂
Quantum mechanics of atoms, bonding, periodic trends, thermodynamics. Research-oriented, not a standard gen chem course. The right foundations before DFT. 🔗 https://www.coursera.org/learn/general-chemistry
4. 𝑰𝒏𝒕𝒓𝒐𝒅𝒖𝒄𝒕𝒊𝒐𝒏 𝒕𝒐 𝑪𝒉𝒆𝒎𝒊𝒔𝒕𝒓𝒚 — 𝑫𝒖𝒌𝒆 𝑼𝒏𝒊𝒗𝒆𝒓𝒔𝒊𝒕𝒚, 𝑪𝒐𝒖𝒓𝒔𝒆𝒓𝒂
Atomic structure, molecular geometry, quantum numbers, bonding. Start here if building from scratch. 🔗 https://www.coursera.org/learn/intro-chemistry
5. 𝑰𝒏𝒕𝒓𝒐𝒅𝒖𝒄𝒕𝒊𝒐𝒏 𝒕𝒐 𝑻𝒉𝒆𝒓𝒎𝒐𝒅𝒚𝒏𝒂𝒎𝒊𝒄𝒔 — 𝑼𝒏𝒊𝒗𝒆𝒓𝒔𝒊𝒕𝒚 𝒐𝒇 𝑴𝒊𝒄𝒉𝒊𝒈𝒂𝒏, 𝑪𝒐𝒖𝒓𝒔𝒆𝒓𝒂
Laws of thermodynamics, entropy, equilibrium, energy transfer. Core physical chemistry background for materials science and DFT. 🔗 https://www.coursera.org/learn/thermodynamics-intro
6. 𝑨𝒕𝒐𝒎𝒊𝒔𝒕𝒊𝒄 𝑪𝒐𝒎𝒑𝒖𝒕𝒆𝒓 𝑴𝒐𝒅𝒆𝒍𝒊𝒏𝒈 𝒐𝒇 𝑴𝒂𝒕𝒆𝒓𝒊𝒂𝒍𝒔 — 𝑴𝑰𝑻 𝑶𝑪𝑾
Full MIT graduate course on DFT for materials science. Lecture notes, problem sets, video lectures. No signup. No certificate but complete content free forever. 🔗 https://ocw.mit.edu/courses/3-320-atomistic-computer-modeling-of-materials-sma-5107-spring-2005/
Suggested order:
Duke → Rice → Michigan → Minnesota → MIT OCW → École Polytechnique DFT.
All free to audit. Certificates available for a small fee. Apply for Coursera financial aid two weeks before your start date. Approval rate is high and covers the full cost.
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