Conclusion

Randomness is useful when controlled well enough to inspect.

You learned how to generate random numbers, use seeds, sample values, shuffle and split data, save small result summaries, store configuration values, and rerun randomized code.

The central habit is:

record what controls the run

For a small randomized experiment, that usually means:

and later:

seed: 7
trials: 100
result: ...

What comes next

The next chapter combines the pieces into small numerical experiments.

You will read or create small data, compute with arrays, plot results, use a configuration record, and save a short summary. That is the first complete scientific Python workflow in this subject.