Welcome to the repository for the Practical Programming in Chemistry exercises. Those exercises offers a comprehensive and hands-on introduction to computer programming, tailored specifically for chemists and chemical engineers. With a focus on Python, this course is designed to equip you with the programming skills necessary to tackle real-world chemical tasks.
The course handout can be found on https://schwallergroup.github.io/practical-programming-in-chemistry/.
This course is designed for individuals with little to no programming experience and focuses on applying programming concepts within the context of chemistry and chemical engineering. Through a series of lessons and hands-on exercises.
Our goal is to make programming accessible and relevant to chemists and chemical engineers, enabling you to automate tasks, analyze data, and enhance your research capabilities.
Below is a table linking to the exercise folders for each week. Navigate to the relevant week to access the exercises.
| Week | Topic | Exercise Link |
|---|---|---|
| 01 | Data types and paths | Week 01 |
| 02 | Jupyter notebooks and Python basics | Week 02 |
| 03 | Advanced Python: file I/O, functions, error handling, and classes. | Week 03 |
| 04 | Numerical operations, data handling, data visualization: numpy, pandas, matplotlib |
Week 04 |
| 05 | RDKit (part I): Reading/Writing, Descriptors, Fingerprints |
Week 05 |
| 06 | RDKit (part II): Substructure matching, Conformer generation |
Week 06 |
| 07 | Making a Python package | Week 07 |
| 08 | Data Acquisition and Cleaning, Web APIs | Week 08 |
| 09 | More packaging; project templates, code testing and coverage. | Week 09 |
| 10 | Visualization and analysis of chemical data (clustering) | Week 10 |
| 11 | Week 11 | |
| 12 | Week 12 |
Happy coding!