Julia has always had the ability to call Python code. For example you can use PyPlot/matplotlib as a plotting backend for Julia.

There is no way to bootstrap a scientific language without leveraging existing ecosystems. But this is a starting point. Whenever someone find a sklearn model to slow, or misses the automatic parallelism that Julia brings, they can just implement the model in Julia, and bit by bit the non-Julia bits get swapped out where it brings a real benefit.