> For the complete documentation index, see [llms.txt](https://docs.dharpa.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.dharpa.org/troubleshooting/tips-for-beginners.md).

# Tips for beginners

## What you need to know

Kiara is a powerful tool for data processing and analysis, but it assumes you have certain foundational skills. This page will help you understand what you need to know and where to learn these skills if you're just starting out with digital humanities methods.

## Essential skills

Kiara requires some competency in, or at least a willingness to use, your computer's Command Line Interface, Python, virtual environments, and Jupyter notebooks. A basic understanding of data processing techniques, the principles of reproducible research, network analysis, and topic modeling will also be a big advantage.

If the detailed guidance available in this documentation is not enough to get you started, we suggest you begin with some introductory tutorials from excellent resources such as [Programming Historian](https://programminghistorian.org/) and [Ranke.2](https://ranke2.uni.lu/).

## Skill levels and what's possible

**Minimum**: Follow step-by-step instructions, create virtual environments, install packages, and run basic Python scripts or notebooks.

**Comfortable**: Modify existing code, understand error messages, debug simple problems, and adapt workflows to your data and research questions.

**Advanced**: Write custom modules, create new processing pipelines, and contribute to the Kiara ecosystem.