Hi, Daniel.
The things you need as prerequisites for the Deep Learning Specialization are:
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Knowledge of basic Linear Algebra. You need to have experience working with vectors and matrices and understand algebraic operations like matrix multiply and transpose. You don’t need to know what an eigenvalue is, though.
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Solid competence as a python programmer. The courses assume that you already know how to program in python. The first course will introduce you to numpy (the linear algebra package for python), but you need to be comfortable with python before you start. E.g. how functions work, flow control constructs (if statements and loops) and python data structures like lists, tuples and dictionaries. All the courses in the DLS series other than Course 3 have programming assignments. They are presented in Jupyter notebooks and there are very good instructions and they give you templates for a lot of the basics so that you don’t have to write everything from scratch, but do you need to complete the key parts of the algorithms.
The courses are also presented by Prof Andrew Ng, so you already know what a great teacher he is. The material is incredibly interesting and the presentation is really excellent. Give it a try and you won’t be disappointed!