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.
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 lecture. Navigate to the relevant week to access the exercises.
| Lecture | Topic | Exercise Link |
|---|---|---|
| 01 | Setup your environment | Lecture01 |
| 02 | GitHub and creating first repositories | Lecture02 |
| 03 | Conda, Jupyter notebooks, and Python basics | Lecture03 |
| 04 | Advanced Python: file I/O, functions, error handling, and classes. | Lecture04 |
| 05 | Numerical operations, data handling, data visualization: numpy, pandas, matplotlib |
Lecture05 |
| 06 | RDKit (part I): Reading/Writing, Descriptors, Fingerprints |
Lecture06 |
| 07 | RDKit (part II): Substructure matching, Conformer generation |
Lecture07 |
| 08 | Making a Python package | Lecture08 |
| 09 | Data Acquisition and Cleaning, Web APIs | Lecture09 |
| 10 | More packaging; project templates, code testing and coverage. | Lecture10 |
| 11 | Visualization and analysis of chemical data (clustering) | Lecture11 |
| 12 | Streamlit | Lecture12 |
| 13 |
We are currently updating last year's course. So, there might be upcoming changes in the schedule.
Happy coding!