# Quick guide: data scientist

The short version of what a data scientist needs on day one: where code runs, where data has to live, and the one habit that keeps a cluster busy.

Source: https://university.eugo.io/resources/quick-guide-data-scientist

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- Kind: Quick guide
- Topics: fundamentals, eugoide, distributed-compute

## Day one

- **Open a session** — Your work happens in EugoIDE, a browser-based notebook environment. Files you save in workspace storage persist between sessions; anything else does not.
- **Run your existing code first** — Before distributing anything, confirm your current analysis runs as-is. Most pandas and NumPy code needs no changes.
- **Learn three API calls** — The distribute decorator turns a function into a distributed task, calling it returns a future, and get() resolves futures. That is enough for most workloads.

## The habit that matters most

- **Build the whole list of futures before waiting on any** — Calling get() inside a loop runs your tasks one at a time. Collect every future first, then call get() once on the list.