MolSSI Education Resources
MolSSI offers 1-2 day workshops as well as online tutorial materials. All tutorials are hosted on GitHub in the MolSSI Education GitHub organization. Workshops and materials here may still be under development. Outside contribution is welcomed and encouraged!
Python Data and Scripting Workshop
Description: The MolSSI Python Data and Scripting workshop is designed for students who are currently involved in, or planning to start computational chemistry research. This workshop is designed to help students develop practical programming skills that will benefit their undergraduate research, and will take students through introductory programming and scripting with Python to version control and sharing their code with others. NO prior programming experience is required.
Best Practices Workshop
Description: Our best practices workshops introduce and promote MolSSI best practices to workshop attendees. This workshop is designed for graduate students, post docs, or advanced undergraduate students. In this course, students create a Python package using best practices and the MolSSI CookieCutter, and host this project on GitHub.
Data Analysis using Python
Description: The Python Data Analysis Tutorials are short stand-alone tutorials, which build on and expand the Python Scripting Workshop. These lessons include introductions to specific libraries including NumPy and pandas.
Object Oriented Programming and Design Patterns
Description:The Object Oriented Programming (OOP) and Design Patterns tutorials provide a brief introduction to good software design principles. These tutorials are designed for graduate students, post docs, or advanced undergraduate students. Students will develop python modules using OOP principles and software design patterns.
Getting Started in Computational Chemistry
Description: A curated list of tutorials for common computational skills that students need to get started in copmutational chemistry research such as use of the terminal, text editors, and remote computing resources.
Description: These lessons introduce basic parallelization techniques and best practices. There are several examples that cover the topic of distributed-memory parallelization using the Message Passing Interface (MPI) and shared-memory parallelization using OpenMP. Examples are provided both in C++ and in Python using the mpi4py wrapper. Both the MPI and OpenMP tutorials begin with simple “Hello World!” codes and culminate in the parallelization of a simple molecular dynamics code.
Quantum Mechanics Tools
Description: The qm-tools workshop introduces several types of quantum chemistry calculations a student might use, including geometry optimizations, inter- and intra-molecular potential energy scans, and energy calculations. Some basic file parsing and data analysis is also discussed.