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This lesson continues with the second workshop on reproducible science, focusing on additional open source tools for researchers and data scientists, such as the R programming language for data science, as well as associated tools like RStudio and R Markdown. Additionally, users are introduced to Python and iPython notebooks, Google Colab, and are given hands-on tutorials on how to create a Binder environment, as well as various containers in Docker and Singularity.

Difficulty level: Beginner
Duration: 1:16:04

This is an in-depth guide on EEG signals and their interaction within brain microcircuits. Participants are also shown techniques and software for simulating, analyzing, and visualizing these signals.

Difficulty level: Intermediate
Duration: 1:30:41
Speaker: : Frank Mazza

In this tutorial on simulating whole-brain activity using Python, participants can follow along using corresponding code and repositories, learning the basics of neural oscillatory dynamics, evoked responses and EEG signals, ultimately leading to the design of a network model of whole-brain anatomical connectivity. 

Difficulty level: Intermediate
Duration: 1:16:10
Speaker: : John Griffiths

This lesson provides a brief overview of the Python programming language, with an emphasis on tools relevant to data scientists.

Difficulty level: Beginner
Duration: 1:16:36
Speaker: : Tal Yarkoni
Course:

An introduction to data management, manipulation, visualization, and analysis for neuroscience. Students will learn scientific programming in Python, and use this to work with example data from areas such as cognitive-behavioral research, single-cell recording, EEG, and structural and functional MRI. Basic signal processing techniques including filtering are covered. The course includes a Jupyter Notebook and video tutorials.

 

Difficulty level: Beginner
Duration: 1:09:16
Speaker: : Aaron J. Newman
Course:

This book was written with the goal of introducing researchers and students in a variety of research fields to the intersection of data science and neuroimaging. This book reflects our own experience of doing research at the intersection of data science and neuroimaging and it is based on our experience working with students and collaborators who come from a variety of backgrounds and have a variety of reasons for wanting to use data science approaches in their work. The tools and ideas that we chose to write about are all tools and ideas that we have used in some way in our own research. Many of them are tools that we use on a daily basis in our work. This was important to us for a few reasons: the first is that we want to teach people things that we ourselves find useful. Second, it allowed us to write the book with a focus on solving specific analysis tasks. For example, in many of the chapters you will see that we walk you through ideas while implementing them in code, and with data. We believe that this is a good way to learn about data analysis, because it provides a connecting thread from scientific questions through the data and its representation to implementing specific answers to these questions. Finally, we find these ideas compelling and fruitful. That’s why we were drawn to them in the first place. We hope that our enthusiasm about the ideas and tools described in this book will be infectious enough to convince the readers of their value.

 

Difficulty level: Intermediate
Duration:
Speaker: :

This is a hands-on tutorial on PLINK, the open source whole genome association analysis toolset. The aims of this tutorial are to teach users how to perform basic quality control on genetic datasets, as well as to identify and understand GWAS summary statistics. 

Difficulty level: Intermediate
Duration: 1:27:18
Speaker: : Dan Felsky

This is a tutorial on using the open-source software PRSice to calculate a set of polygenic risk scores (PRS) for a study sample. Users will also learn how to read PRS into R, visualize distributions, and perform basic association analyses. 

Difficulty level: Intermediate
Duration: 1:53:34
Speaker: : Dan Felsky

This lesson provides a short reel on who we are, what we're doing and why we're doing it.

Difficulty level: Beginner
Duration: 2:38
Speaker: :

In this webinar, educators currently implementing collaborative annotation in their classrooms discuss their experiences with collaborative annotation and using Hythothes.is and Canvas App.

Difficulty level: Beginner
Duration: 53:14
Speaker: : Jeremy Dean

This tutorial provides an overview of how to use the feature of Hypothes.is.

Difficulty level: Beginner
Duration: 09:30
Speaker: :

This lesson gives a brief overview of the Hypothes.is functionality from an end user's perspective.

Difficulty level: Beginner
Duration: 5:36
Speaker: : Heather Staines

This video will teach you the basics of navigating the Open Science Framework and creating your first projects.

Difficulty level: Beginner
Duration: 2:11
Speaker: :

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.

Difficulty level: Beginner
Duration: 55:02
Speaker: : Ian Sullivan

This webinar will introduce how to use the Open Science Framework (OSF) in a classroom setting.

Difficulty level: Beginner
Duration: 32:01

This lesson provides instruction on how to organize related projects with OSF features such as links, forks, and templates.

Difficulty level: Beginner
Duration: 51:14
Speaker: : Ian Sullivan

This webinar will introduce the integration of JASP Statistical Software with the Open Science Framework (OSF).

Difficulty level: Beginner
Duration: 30:56
Speaker: : Alexander Etz

This lesson describes the value of version control, as well as how to do so with your own files and data on OSF. 

Difficulty level: Beginner
Duration: 22:07

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

Difficulty level: Beginner
Duration: 34:53
Speaker: : Thomas Kluyver

JupyterHub is a simple, highly extensible, multi-user system for managing per-user Jupyter Notebook servers, designed for research groups or classes. This lecture covers deploying JupyterHub on a single server, as well as deploying with Docker using GitHub for authentication.

Difficulty level: Beginner
Duration: 1:36:27
Speaker: : Thomas Kluyver