This course provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function. We will explore the computational principles governing various aspects of vision, sensory-motor control, learning, and memory. Specific topics that will be covered include representation of information by spiking neurons, processing of information in neural networks, and algorithms for adaptation and learning. We will make use of Matlab/Octave/Python demonstrations and exercises to gain a deeper understanding of concepts and methods introduced in the course. The course is primarily aimed at third- or fourth-year undergraduates and beginning graduate students, as well as professionals and distance learners interested in learning how the brain processes information.
이 강좌에 대하여
귀하가 습득할 기술
Founded in 1861, the University of Washington is one of the oldest state-supported institutions of higher education on the West Coast and is one of the preeminent research universities in the world.
- 5 stars71.11%
- 4 stars22.67%
- 3 stars3.93%
- 2 stars1.55%
- 1 star0.72%
컴퓨터 신경 과학의 최상위 리뷰
Pretty good. A bit of mathematical ambiguity and lax notational conventions, but the course content was solid and presented clearly.
I really enjoyed this course and think that there was a good variety of material that allowed people of many different backgrounds to take at least one thing away from this.
A very nice introduction to Computational Neuroscience world. The main course advantage is the matching between theory and practice (programming).
Brilliant course. For a HS student the math was challenging, but the quizzes and assignments were perfect. The tutorials and supplementary materials are super helpful. All in all, I loved it.
자주 묻는 질문
강의 및 과제를 언제 이용할 수 있게 되나요?
이 수료증을 구매하면 무엇을 이용할 수 있나요?
재정 지원을 받을 수 있나요?
궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.