There is hardly any pure CS like it appears to be the US case.
All Informatics degrees are actually a mix of CS and Software Engineering.
For pure theoretical CS one needs to go for a Maths degree with focus on computation (after the third year).
EDIT: Typo the => be
I agree that numerical computing algorithms are indeed very important topics. I was very excited when I learned about them (then took Numerical Math 2, and finally met my match, was above my ability to learn in one block).
I do think that it was a good idea to teach Algorithms first, though. I don't think I would have appreciated Numerical Math as much if I had taken it in my first year, but Algorithms was pretty accessible, cool, and precisely the sort of thing I had imagined studying Computer Science to be like.
Dear 'All CS Departments of the World':
Please stop fooling your students in the 'Intro to Algorithms' class, and just rename it to 'Intro to Combinatorial Algorithms'. Because that's what you teach, and you completely ignore the arguably bigger area of 'Intro to Numerical Algorithms'. Numerical Algorithms, that are not only the basis of pretty much every branch of computational science (comp. physics, comp. chemistry, comp. biology, comp. civil engineering, comp. mechanical eng., comp. electrical eng., comp economics, comp. statistics, and on and on and on), but it's also one of the weakest link for a CS graduate to transition to Machine Learning and Data Science.
Or you could keep the course title, but upgrade the class, by teaching 50% of it as 'Algorithms and Data Structures', and 50% as 'Numerical Methods and Scientific Computing'.
Unrelated to above but relevant to the thread: Allen Downey and his team at Olin College are doing things worth looking into. (His Google techtalk: https://www.youtube.com/watch?v=iZuhWo0Nv7o)