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Medford Group Graduate Training
VIP
VIP Materials
VIP Course Syllabus
Big Data & Quantum Mechanics
DFT adsorption energy reproducibility project
Training Materials
Introduction to Linux and High-Performance Computing
Exercises
Introduction to Basic Python Tools
Introduction to Python programming
Numpy - multidimensional data arrays
SciPy - Library of scientific algorithms for Python
matplotlib - Plotting in Python
Exercises
Introduction to Manipulating Atoms in Python
Intro to Building Structures with ASE
Intro to ASE Calculators
Exercises - Intro
Exercises - Calculators
Running Density Functional Theory on PACE
Running QE on PACE
Running a simple DFT calculation on PACE Supercomputer Cluster
Exercises
Applications of Density Functional Theory
Adsorption energy calculation using DFT
Adsorption energy from DFT
Exercises
Introduction to Density Functional Theory
Understanding and Optimizing DFT Calculations
Convergence of Computational Parameters
Exercises
Intro to Regression and High Dimensional Data
Non-Parametric Models
Complexity Optimization
High Dimensional Data
Dimensionality Reduction
Exercises
Intro to Classification and Generative Models
Classification Overview
Generalized Linear Models
Alternate classification methods
Clustering
Generative Models
Exercises
Appendix
Appendix
Basics of Searching and Reading Scientific Literature
Create DFT Environments
Gas formation energy calculation using DFT
Referencing Binding Energies
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