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This lesson provides a primer on linear algebra, aiming to demonstrate how such operations are fundamental to many data science. 

Difficulty level: Beginner
Duration: 5:38
Speaker: : Barton Poulson

In this lesson, users will learn about linear equation systems, as well as follow along some practical use cases.

Difficulty level: Beginner
Duration: 5:24
Speaker: : Barton Poulson

This talk gives a primer on calculus, emphasizing its role in data science.

Difficulty level: Beginner
Duration: 4:17
Speaker: : Barton Poulson

This lesson clarifies how calculus relates to optimization in a data science context. 

Difficulty level: Beginner
Duration: 8:43
Speaker: : Barton Poulson

This lesson covers Big O notation, a mathematical notation that describes the limiting behavior of a function as it tends towards a certain value or infinity, proving useful for data scientists who want to evaluate their algorithms' efficiency.

Difficulty level: Beginner
Duration: 5:19
Speaker: : Barton Poulson

This lesson serves as a primer on the fundamental concepts underlying probability. 

Difficulty level: Beginner
Duration: 7:33
Speaker: : Barton Poulson

Serving as good refresher, this lesson explains the maths and logic concepts that are important for programmers to understand, including sets, propositional logic, conditional statements, and more.

This compilation is courtesy of freeCodeCamp.

Difficulty level: Beginner
Duration: 1:00:07
Speaker: : Shawn Grooms

This lesson provides a useful refresher which will facilitate the use of Matlab, Octave, and various matrix-manipulation and machine-learning software.

This lesson was created by RootMath.

Difficulty level: Beginner
Duration: 1:21:30
Speaker: :
Course:

This lecture covers the description and characterization of an input-output relationship in a information-theoretic context. 

Difficulty level: Beginner
Duration: 1:35:33

This lesson is part 1 of 2 of a tutorial on statistical models for neural data.

Difficulty level: Beginner
Duration: 1:45:48
Speaker: : Jonathan Pillow

This lesson is part 2 of 2 of a tutorial on statistical models for neural data.

Difficulty level: Beginner
Duration: 1:50:31
Speaker: : Jonathan Pillow

From the retina to the superior colliculus, the lateral geniculate nucleus into primary visual cortex and beyond, this lecture gives a tour of the mammalian visual system highlighting the Nobel-prize winning discoveries of Hubel & Wiesel.

Difficulty level: Beginner
Duration: 56:31
Speaker: : Clay Reid

From Universal Turing Machines to McCulloch-Pitts and Hopfield associative memory networks, this lecture explains what is meant by computation.

Difficulty level: Beginner
Duration: 55:27
Speaker: : Christof Koch

In this lesson you will learn about ion channels and the movement of ions across the cell membrane, one of the key mechanisms underlying neuronal communication. 

Difficulty level: Beginner
Duration: 25:51
Speaker: : Carl Petersen

This lecture gives an introduction to the types of glial cells, homeostasis (influence of cerebral blood flow and influence on neurons), insulation and protection of axons (myelin sheath; nodes of Ranvier), microglia and reactions of the CNS to injury.

Difficulty level: Beginner
Duration: 40:32

This lecture covers the history of behaviorism and the ultimate challenge to behaviorism. 

Difficulty level: Beginner
Duration: 1:19:08

This lecture covers various learning theories.

Difficulty level: Beginner
Duration: 1:00:42

How does the brain learn? This lecture discusses the roles of development and adult plasticity in shaping functional connectivity.

Difficulty level: Beginner
Duration: 1:08:45
Speaker: : Clay Reid

This lesson provides an overview of how to construct computational pipelines for neurophysiological data using DataJoint.

Difficulty level: Beginner
Duration: 17:37
Speaker: : Dimitri Yatsenko

This lesson covers the ionic basis of the action potential, including the Hodgkin-Huxley model. 

Difficulty level: Beginner
Duration: 28:29
Speaker: : Carl Petersen