Download Computational Chemistry with Python: Essential Programming 2026
Computational Chemistry with Python: Essential Programming video corse download, Master Python automation for Gaussian: convert files, extract data, and streamline computational workflows. Master advanced molecular file conversion and data processing techniques using Python automation. This guide teaches you how to efficiently work with common computational chemistry formats such as XYZ, GJF, PDB, and LOG files, while extracting important information from Gaussian calculations, including SCF energies, Gibbs free energies, vibrational frequencies, and IR intensities. Process multiple calculation results automatically and reduce hours of manual analysis to just a few seconds.
Develop powerful Python scripts for molecular structure manipulation and computational workflow automation. Learn how to calculate molecular distances, adjust atomic orientations, align structures with specific planes, move molecules along coordinate axes, and generate molecular enantiomers. Create automated workflows that transform optimized geometries into ready-to-use input files for frequency calculations, NBO studies, molecular orbital analysis, and polarizability computations.
Turn raw computational chemistry results into clear and professional visualizations using Python libraries such as NumPy and Matplotlib. Generate IR spectra, analyze energy convergence behavior, and create high-quality scientific plots suitable for research papers, presentations, and advanced molecular modeling projects.
What you’ll learn
- Master file format conversions between XYZ, GJF, PDB, and LOG files to streamline your Gaussian computational workflow
- Extract and analyze energies, frequencies, and geometries from Gaussian log files using NumPy and automated Python scripts
- Perform coordinate transformations: center molecules, calculate bond distances, reorient structures, and generate mirror images
- Create IR spectrum plots and energy convergence graphs from Gaussian output data for publication-ready visualizations
- Automate Gaussian input generation for frequency, NBO, orbital, and polarizability calculations from optimized geometries
Course content
- Introduction
- Cartesian Coordinates from the output file and export them in xyz file
- calculate distance between atoms and selectively printing van der Waals distance
- Energies of intermediate geometries during optimization
- Translation of coordinates
- File Format Interconversion
- Converting one enantiomer to the other
- Analyzing bulk Gaussian input and output files through python
- Generating property files from the optimized structures through python
Who this course is for
- Computational chemists and researchers using Gaussian software for quantum chemical calculations
- Graduate students and postdocs in chemistry who need to automate their computational workflows
- Theoretical chemistry researchers processing multiple molecular structures and Gaussian calculations
- Chemistry professors and educators teaching computational methods and molecular modeling
Course details
- Video quality: MP4 | Video: h264, 1280 × 720
- Audio quality: Audio: AAC, 44.1 KHz, 2 Ch
- Last updated 07/2026
- Video duration: 3h 25m
- Number of lessons: 09 sections, 24 lectures
- Language: Language: English
- Compressed file size: 2.9 GB
