personally I think it's more important to know datastructures and their implicit algorithmic constraints.
For example: time ranges what is the most efficient datastructure and why ?
A sorted Array with binary search has O(log(n)) for lookup O(1) to check it's siblings but the insert will take O(n). To understand those basics in a common app scenario is more important that knowing the huffman compression.
So the next thing should be sorting algorithms but not by heart more about space and time complexity and that there is a difference.
And after that you have A* path finding ofc and so on but those are specialized ones the datastructures are basics and the sorts are basics.
Even Sort we could argue about if we need to know all of their attributes. But still you're more likely to get confronted with those than with others.
As soon as we go to graphs things get more interesting but this already breakes the scope of 10 because every datastructure has at least CRUD so there are 4 algorithms per structure. > 10