This is one of the level 2 core courses required as part of a mathematics major. For statistics majors, students have the choice of picking between this, and MATH2521/2621 (complex analysis). Differential equations are something students are very accustomed to from first year; they're essentially just trying to find a function that satisfies an equation, which somehow relates the function to its own derivatives. (Can of course, be higher than the first derivative.) This course does introduce significantly more techniques than in first year.
This course is introduced as a toolbox course (which, I note throws off many pure-math wired students). As with every math course, some element of proof is required. But the main focus of this course is in applying various techniques taught to finding/constructing solutions (or solution representations) to differential equations. For the most part, this course is therefore computational. They try to minimise it in this course, but every once in a while the ability to handle demanding algebraic computations becomes important.
But of course, in terms of computations, what they emphasise on is how well you know the techniques. I saw pretty much every technique get examined (power series, reduction of order, variation of parameters in the assignment, Sturm-Liouville theory, formally self adjoint operators, dynamical systems, Steklov eigenpairs, ...).
The course is absolutely crucial to applied mathematics majors. Anyone considering applied mathematics is strongly advised to take this course in second year, as it is a prerequisite for several level 3 applied courses.
The workshops were basically the assignments as far as I was aware. I think they were renamed just to emphasise the peer review component of it. Which wasn't too bad, in the grand scheme of things.
I was originally going to give this course a 4/5 for the content, but then Jan actually boiled the egg in class this year. That was a 0.5 rating in itself. (Students that will take/have taken the course will know what I mean here.)