This is a short course covering the basics of Dynamical Systems Theory – specifically as used in Computational Neuroscience. The material covers the basics of the underlying mathematics, together with some of the broader physical theories surrounding the field. The content is organised in short sections, each intended as a self-contained module.
This course is intended for UG or PG students enrolled in clinical, biological, or psychology degrees who have not had a formal higher education in mathematics or physics since A-Levels or GCSEs. The material covered is not intended for students enrolled in engineering, mathematics, or physical science degrees, as these will be familiar with the topics already.
There is no assumed knowledge in the mathematics or physics covered in this course. A basic education (A-level or GCSE) in mathematics or physics is helpful but not required. Any material not covered in detail is linked to external sources within the course.
Upon completion of the course, students will be in a position to better tackle the external source material we link to in order to gain a more in-depth understanding of the mathematics and physical theories upon which the methods in Computational Neuroscience are based.
King’s Prize Fellowship | Dept of Neuroimaging | King's College London
Learning Technologist | Learning Hub | King's Health Partners
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