The materials that you should read and study in preparing for examinations on this course consist of lecture slides and solutions of exercises, with exercise problems. It is useful and helpful to read also the materials that are available on the subpage 'Materials'. They consist of two chapters (6 and 13) from Haykin's book (1998) and two journal articles on independent component analysis and extreme learning machines, plus a couple of pages explaining convolutional networks.
On the lecture slides the books K.-L. Du and M. Swamy, "Neural Networks and Statistical Learning", Springer 2014, and S. Haykin, "Neural Networks: A Comprehensive Foundation", Prentice-Hall 1998, are often referred to, but you need not acquire and read them. They serve as references and background materials from which you can find more information if necessary.
No course materials and notes on them are allowed in the examinations. Also functions calculators etc. and collections of mathematical formulas are not allowed in the examinations, but you will not need them.