This lecture covers an Introduction to neuron anatomy and signaling, and different types of models, including the Hodgkin-Huxley model.

This lecture describes non-spiking simple neuron models used in artificial neural networks and machine learning.

A short reel on who we are, what we're doing and why we're doing it

This video will teach you the basics of navigating the OSF, a free research management tool, and creating your first projects.

This webinar walks you through the basics of creating an OSF project, structuring it to fit your research needs, adding collaborators, and tying your favorite online tools into your project structure.

This webinar will introduce how to use the Open Science Framework (OSF; https://osf.io) in a Classroom. The OSF is a free, open source web application built to help researchers manage their workflows. The OSF is part collaboration tool, part version control software, and part data archive. The OSF connects to popular tools researchers already use, like Dropbox, Box, Github and Mendeley, to streamline workflows and increase efficiency.

Organizing related projects with Links, Forks, and Templates.

This webinar will introduce the integration of JASP Statistical Software (https://jasp-stats.org/) with the Open Science Framework (OSF; https://osf.io). The OSF is a free, open source web application built to help researchers manage their workflows

1. How keeping track of the different file versions is important for efficient reproducible research practices
2. How version control works on the OSF
3. How researchers can view and download previous versions of files

This lecture focuses on where and how Jupyter notebooks can be used most effectively for education

This tutorial talks about how to upload and version your data in OpenNeuro.org

This tutorial shows how to share your data in OpenNeuro.org

This tutorial shows how to run analysis in OpenNeuro.org

This lecture covers an Introduction to neuron anatomy and signaling, and different types of models, including the Hodgkin-Huxley model.

This lecture describes non-spiking simple neuron models used in artificial neural networks and machine learning.

Introductory presentation on how data science can help with scientific reproducibility.

FAIR principles and methods currently in development for assessing FAIRness.

The probability of a hypothesis, given data.

Why math is useful in data science.

Why statistics are useful for data science.