This lecture will provide an overview of the INCF Training Suite, a collection of tools that embraces the FAIR principles developed by members of the INCF Community. This will include an overview of TrainingSpace, Neurostars, and KnowledgeSpace.

This session will include presentations of infrastructure that embrace the FAIR principles developed by members of the INCF Community. This lecture provides an overview and demo of the Canadian Open Neuroscience Platform (CONP).

This lecture contains an overview of the China-Cuba-Canada neuroinformatics ecosystem for Quantitative Tomographic EEG Analysis (qEEGt).

This session provides users with an introduction to tools and resources that facilitate the implementation of FAIR in their research.

This lesson provides an overview of self-supervision as it relates to neural data tasks and the Mine Your Own vieW (MYOW) approach.

In this talk, you will learn how brainlife.io works, and how it can be applied to neuroscience data.

This lecture covers the IBI Data Standards and Sharing Working Group, including its history, aims, and projects.

This session covers the framework of the International Brain Lab (IBL) and the data architecture used for this project.

This session will include presentations of infrastructure that embrace the FAIR principles developed by members of the INCF Community.

This lecture provides an overview of The Virtual Brain Simulation Platform.

This lesson gives an introduction to the Mathematics chapter of Datalabcc's Foundations in Data Science series.

This lesson serves a primer on elementary algebra.

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

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

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

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

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.

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

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.

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.

This lecture covers a lot of post-war developments in the science of the mind, focusing first on the cognitive revolution, and concluding with living machines.