# VIP Materials

Welcome to the VIP portion of the Medford group training materials. Here, you will find a brief enumeration of the lectures and exercises that you will be expected to complete as part of the training sub-team. You are more than welcome to explore the additional content, and you may find it helpful to return here after you've joined a sub-team for additional instruction. Keep in mind that you *must* complete the exercises enumerated here. 

## Lectures
- HPC: [Introduction to Linux and High-Performance Computing](linux-hpc)
- PY: [Introduction to Basic Python Tools](basic-python)
- ASE: [Introduction to Manipulating Atoms in Python](manipulating-atoms)
- PACE: [Running DFT on PACE](dft-on-pace)
- ADS: [Adsorption energy from DFT](ads-sparc)
- DFT: [Introduction to Density Functional Theory](intro-dft)
- CONV: [Understanding and Optimizing DFT calculations](nuts-bolts)
- [Non-Parametric Models](non-para-models)**
- [High Dimensional Data](high-dim-data)**
- [Dimensionality Reduction](dim-red)**

** Machine Learning lectures are provided for your information only and will not be lectured on this semester.

## Exercises
- [HPC.1-4](linux-ex)
- [PY.1-5](python-ex)
- [ASE.1](ase-intro-ex) and [ASE.2-3](ase-calcs-ex)
- [PACE.1-3](pace-ex)
- [ADS.1-3](ads-ex)
- [CONV.1-3](conv-ex)

This course is structured to provide an accelerated introduction to actually performing DFT calculations first, before providing the crucial theoretical background after you have established the requistite hands-on experience. Our hope that this "flipped" structure (do first, learn later) will ground the sometimes obtuse concepts from quantum mechanics within a more appraochable context. Therefore, it is absolutely critical that you complete all of the practical exercises in a timely fashion. We encourage you to first get through the [Intro to DFT](intro-dft) section before moving on to the [convergence](nuts-bolts) section, as this will give you a good basis for understanding why parameter convergence is important.