CS-503: Visual intelligence : machines and minds

Related MOOCs (26)

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Optimization: principles and algorithms - Network and discrete optimization

Introduction to network optimization and discrete optimization

Optimization: principles and algorithms - Unconstrained nonlinear optimization

Introduction to unconstrained nonlinear optimization, Newton’s algorithms and descent methods.

Optimization: principles and algorithms - Unconstrained nonlinear optimization

Introduction to unconstrained nonlinear optimization, Newton’s algorithms and descent methods.

IoT Systems and Industrial Applications with Design Thinking

The first MOOC to provide a comprehensive introduction to Internet of Things (IoT) including the fundamental business aspects needed to define IoT related products.

Neuronal Dynamics - Computational Neuroscience of Single Neurons

The activity of neurons in the brain and the code used by these neurons is described by mathematical neuron models at different levels of detail.

Neuronal Dynamics 2- Computational Neuroscience: Neuronal Dynamics of Cognition

This course explains the mathematical and computational models that are used in the field of theoretical neuroscience to analyze the collective dynamics of thousands of interacting neurons.

Neuronal Dynamics 2- Computational Neuroscience: Neuronal Dynamics of Cognition

This course explains the mathematical and computational models that are used in the field of theoretical neuroscience to analyze the collective dynamics of thousands of interacting neurons.

Neuronal Dynamics - Computational Neuroscience of Single Neurons

The activity of neurons in the brain and the code used by these neurons is described by mathematical neuron models at different levels of detail.

Digital Signal Processing I

Basic signal processing concepts, Fourier analysis and filters. This module can be used as a starting point or a basic refresher in elementary DSP

Digital Signal Processing II

Adaptive signal processing, A/D and D/A. This module provides the basic tools for adaptive filtering and a solid mathematical framework for sampling and quantization

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