Lessons

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Mathematics: Bayes' theorem
Course:
Foundations of Data Science

The probability of a hypothesis, given data.

Difficulty level: Beginner
Duration: 7:57
Speaker: : Barton Poulson
Mathematics: Next steps
Course:
Foundations of Data Science

Why math is useful in data science.

Difficulty level: Beginner
Duration: 1:35
Speaker: : Barton Poulson
Statistics (intro)
Course:
Foundations of Data Science

Why statistics are useful for data science.

Difficulty level: Beginner
Duration: 4:01
Speaker: : Barton Poulson
Statistics: Exploration overview
Course:
Foundations of Data Science

Statistics is exploring data.

Difficulty level: Beginner
Duration: 2:23
Speaker: : Barton Poulson
Statistics: Exploratory graphics
Course:
Foundations of Data Science

Graphical data exploration

Difficulty level: Beginner
Duration: 8:01
Speaker: : Barton Poulson
Statistics: Exploratory statistics
Course:
Foundations of Data Science

Numerical data exploration

Difficulty level: Beginner
Duration: 5:05
Speaker: : Barton Poulson
Statistics: Descriptive statistics
Course:
Foundations of Data Science

Simple description of statistical data.

Difficulty level: Beginner
Duration: 10:16
Speaker: : Barton Poulson
Statistics: Hypothesis testing
Course:
Foundations of Data Science

Basics of hypothesis testing.

Difficulty level: Beginner
Duration: 06:04
Speaker: : Barton Poulson
Neuroscience Gateway (NSG)
Course:
NeuroTools Webinar series

Enabling neuroscience research using high performance computing

Difficulty level: Beginner
Duration: 39:27
Speaker: : Subha Sivagnanam
Introduction to software engineering for non-ICT specialists
Course:
Introduction to information and communications technology (ICT) for non-specialists

Lecture on the most important concepts in software engineering

Difficulty level: Beginner
Duration: 32:59
Speaker: : Jeff Muller
The database of Genotypes and Phenotypes (dbGAP)
Course:
NeuroTools Webinar series
Difficulty level: Beginner
Duration: 48:22
Speaker: : Michael Feolo
Welcome and introduction to the INCF short course
Course:
INCF Short course: Introduction to neuroinformatics

This lecture covers an introduction to neuroinformatics and its subfields, the content of the short course and future neuroinformatics applications.

Difficulty level: Beginner
Duration: 34:27
Speaker: : Marja-Leena Linne
The action potential
Course:
Computational neuroscience: the basics

The ionic basis of the action potential, including the Hodgkin Huxley model. 

Difficulty level: Beginner
Duration: 28:29
Speaker: : Carl Petersen
Introduction to Cellular Mechanisms of Brain Function
Course:
Biophysical models

Introduction to the course Cellular Mechanisms of Brain Function.

Difficulty level: Beginner
Duration: 12:20
Speaker: : Carl Petersen
The action potential
Course:
Introduction to computational neuroscience

The ionic basis of the action potential, including the Hodgkin Huxley model. 

Difficulty level: Beginner
Duration: 28:29
Speaker: : Carl Petersen
Introduction to Cellular Mechanisms of Brain Function
Course:
Cellular Mechanisms of Brain Function

Introduction to the course Cellular Mechanisms of Brain Function.

Difficulty level: Beginner
Duration: 12:20
Speaker: : Carl Petersen
The cell membrane
Course:
Cellular Mechanisms of Brain Function

The composition of the cell membrane.

Difficulty level: Beginner
Duration: 14:46
Speaker: : Carl Petersen
Cable properties
Course:
Cellular Mechanisms of Brain Function

Spatiotemporal dynamics of the membrane potential.

Difficulty level: Beginner
Duration: 19:14
Speaker: : Carl Petersen
Whole-cell recordings
Course:
Cellular Mechanisms of Brain Function

Action potential initiation and propagation.

Difficulty level: Beginner
Duration: 09:13
Speaker: : Carl Petersen
Synaptic transmission
Course:
Cellular Mechanisms of Brain Function

Synaptic transmission and neurotransmitters

Difficulty level: Beginner
Duration: 28:22
Speaker: : Carl Petersen

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