This workshop adapts the Python Software Carpentry curriculum to focus on best practices for programming in research. Participants will not only learn core Python fundamentals but also explore how to structure reproducible, maintainable, and robust code for research purposes. In addition, the workshop includes a session on running Python scripts from the terminal and dedicates time on Day 2 for getting to know the 4TU.ResearchData repository.
Note: This workshop is still in pilot mode so the actual syllabus may have slight changes for the workshop instance but overall the learning objectives are the same.
Course instances
Dates and locations to be announced.
Learning objectives
By the end of this workshop, participants will be able to:
- Understand Python fundamentals and apply them to research-related problems, namely , utilizes libraries (e.g., NumPy and Pandas) for data manipulation in research.
- Write clean, modular, and well-documented code following best practices
- Run Python scripts from the terminal
- Familiarize with the 4TU.ResearchData repository for data and software long term deposit.
Syllabus/Curriculum overview
Day 1
- Morning session (09:30 – 12:30):
- Welcome & introduction:
- Overview of workshop goals and the importance of reproducibility in research.
- Environment setup & Python fundamentals:
- Setting up Python (using Jupyterlab).
- Core Python topics: data types, variables, for loops, making choices on a case study of analysing a small dataset.
- Welcome & introduction:
- Afternoon session (13:30 – 16:00):
- Creating functions
- Tyding things up
Day 2
- Morning & early afternoon (09:30 – 14:30):
- Introduction to the command line.
- Modify our mini project to run from the terminal with various parameters
- Afternoon session (14:45 – 16:00):
- Overview of the repository system
- Best practices for software and data sharing
Prerequisites
- Basic familiarity with computers and navigating the command line.
- No prior programming experience is required; however, a willingness to engage in hands-on exercises and learn new concepts is essential.
- Participants should have Python installed on their laptops (installation instructions will be provided prior to the workshop).
Target audience
This workshop is designed for:
- Researchers, graduate students, and professionals in academic or scientific fields seeking to integrate programming into their research.
- Individuals who are new to Python or programming and wish to learn to apply these skills in a research context.
Instructors
Resources
Participants are encouraged to bring their own laptops for hands-on exercises. Pre-workshop installation guides, sample datasets, and additional online resources will be provided.