Course:

The probability of a hypothesis, given data.

Difficulty level: Beginner

Duration: 7:57

Speaker: : Barton Poulson

Course:

Why math is useful in data science.

Difficulty level: Beginner

Duration: 1:35

Speaker: : Barton Poulson

Course:

Why statistics are useful for data science.

Difficulty level: Beginner

Duration: 4:01

Speaker: : Barton Poulson

Course:

Statistics is exploring data.

Difficulty level: Beginner

Duration: 2:23

Speaker: : Barton Poulson

Course:

Graphical data exploration

Difficulty level: Beginner

Duration: 8:01

Speaker: : Barton Poulson

Course:

Numerical data exploration

Difficulty level: Beginner

Duration: 5:05

Speaker: : Barton Poulson

Course:

Simple description of statistical data.

Difficulty level: Beginner

Duration: 10:16

Speaker: : Barton Poulson

Course:

Basics of hypothesis testing.

Difficulty level: Beginner

Duration: 06:04

Speaker: : Barton Poulson

Course:

Enabling neuroscience research using high performance computing

Difficulty level: Beginner

Duration: 39:27

Speaker: : Subha Sivagnanam

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

Difficulty level: Beginner

Duration: 1:30:45

Speaker: : Maryann Martone

Course:

Introduction to reproducible research. The lecture provides an overview of the core skills and practical solutions required to practice reproducible research. This lecture was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Beginner

Duration: 1:25:17

Speaker: : Fernando Perez

Course:

This lecture was part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Beginner

Duration: 1:03:07

Speaker: : Russell Poldrack

Course:

This lecture was part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Beginner

Duration: 55:39

Speaker: : Angela Laird

This lecture covers describing and characterizing an input-output relationship.

Difficulty level: Beginner

Duration: 1:35:33

Speaker: : Jonathan D. Victor

Course:

Part 1 of 2 of a tutorial on statistical models for neural data

Difficulty level: Beginner

Duration: 1:45:48

Speaker: : Jonathan Pillow

Course:

Part 2 of 2 of a tutorial on statistical models for neural data.

Difficulty level: Beginner

Duration: 1:50:31

Speaker: : Jonathan Pillow

Course:

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

Course:

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

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

Difficulty level: Beginner

Duration: 25:51

Speaker: : Carl Petersen

Course:

The "connectome" is a term, coined in the past decade, that has been used to describe more than one phenomenon in neuroscience. This lecture explains the basics of structural connections at the micro-, meso- and macroscopic scales.

Difficulty level: Beginner

Duration: 1:13:16

Speaker: : Clay Reid

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