Computational Neuroscience
Key Takeaways
Explores computational methods for understanding nervous systems and determining how they function, covering vision, sensory-motor control, learning, and memory
Original Description
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.
Watch on External: Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
Related Reads
📰
📰
📰
📰
Evolving Algorithms: Next-Generation AI in Predictive Analytics
Dev.to · Fu'ad Husnan
Architecting for the Future: A Blueprint for Model-Agnostic, Business-Ready AI
Medium · AI
The Recommender System Pipeline: An End-to-End Overview
Medium · AI
The Recommender System Pipeline: An End-to-End Overview
Medium · Machine Learning
🎓
Tutor Explanation
DeepCamp AI