The probability of a hypothesis, given data.

Why math is useful in data science.

Why statistics are useful for data science.

Statistics is exploring data.

Graphical data exploration

Numerical data exploration

Simple description of statistical data.

Basics of hypothesis testing.

This lecture covers modeling the neuron in silicon, modeling vision and audition and sensory fusion using a deep network. 

Presentation of a simulation software for spatial model neurons and their networks designed primarily for GPUs.

Presentation of past and present neurocomputing approaches and hybrid analog/digital circuits that directly emulate the properties of neurons and synapses.

Presentation of the Brian neural simulator, where models are defined directly by their mathematical equations and code is automatically generated for each specific target.

This lecture covers structured data, databases, federating neuroscience-relevant databases, ontologies. 

Introduction to the course Cellular Mechanisms of Brain Function.

Introduction to the course Cellular Mechanisms of Brain Function.

Ion channels and the movement of ions across the cell membrane.

Action potential initiation and propagation.

Synaptic transmission and neurotransmitters

Introduction to neurons, synaptic transmission, and ion channels.

2nd part of the lecture. Introduction to cell receptors and signalling cascades