Skip to main content

This hands-on tutorial walks you through DataJoint platform, highlighting features and schema which can be used to build robost neuroscientific pipelines. 

Difficulty level: Beginner
Duration: 26:06
Speaker: : Milagros Marin

In this hands-on session, you will learn how to explore and work with DataLad datasets, containers, and structures using Jupyter notebooks. 

Difficulty level: Beginner
Duration: 58:05

This lesson gives an in-depth introduction of ethics in the field of artificial intelligence, particularly in the context of its impact on humans and public interest. As the healthcare sector becomes increasingly affected by the implementation of ever stronger AI algorithms, this lecture covers key interests which must be protected going forward, including privacy, consent, human autonomy, inclusiveness, and equity. 

Difficulty level: Beginner
Duration: 1:22:06
Speaker: : Daniel Buchman

This lesson describes a definitional framework for fairness and health equity in the age of the algorithm. While acknowledging the impressive capability of machine learning to positively affect health equity, this talk outlines potential (and actual) pitfalls which come with such powerful tools, ultimately making the case for collaborative, interdisciplinary, and transparent science as a way to operationalize fairness in health equity. 

Difficulty level: Beginner
Duration: 1:06:35
Speaker: : Laura Sikstrom

This lesson contains both a lecture and a tutorial component. The lecture (0:00-20:03 of YouTube video) discusses both the need for intersectional approaches in healthcare as well as the impact of neglecting intersectionality in patient populations. The lecture is followed by a practical tutorial in both Python and R on how to assess intersectional bias in datasets. Links to relevant code and data are found below. 

Difficulty level: Beginner
Duration: 52:26

In this lesson, while learning about the need for increased large-scale collaborative science that is transparent in nature, users also are given a tutorial on using Synapse for facilitating reusable and reproducible research. 

Difficulty level: Beginner
Duration: 1:15:12
Speaker: : Abhi Pratap

This lecture discusses what defines an integrative approach regarding research and methods, including various study designs and models which are appropriate choices when attempting to bridge data domains; a necessity when whole-person modelling. 

Difficulty level: Beginner
Duration: 1:28:14
Speaker: : Dan Felsky

This lecture provides an introduction to Plato’s concept of rationality and Aristotle’s concept of empiricism, and the enduring discussion between rationalism and empiricism to this day.

Difficulty level: Beginner
Duration: 1:13:45

This lecture goes into further detail about the hard problem of developing a scientific discipline for subjective consciousness.

Difficulty level: Beginner
Duration: 58:03

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.

Difficulty level: Beginner
Duration: 2:24:35

This lesson gives a brief introduction to the course Neuroscience for Machine Learners (Neuro4ML). 

Difficulty level: Beginner
Duration: 1:25
Speaker: : Dan Goodman

This lesson covers the history of neuroscience and machine learning, and the story of how these two seemingly disparate fields are increasingly merging. 

Difficulty level: Beginner
Duration: 12:25
Speaker: : Dan Goodman

In this lesson, you will learn about the current challenges facing the integration of machine learning and neuroscience. 

Difficulty level: Beginner
Duration: 5:42
Speaker: : Dan Goodman

This lecture provides an overview of depression (epidemiology and course of the disorder), clinical presentation, somatic co-morbidity, and treatment options.

Difficulty level: Beginner
Duration: 37:51

In this lesson, you will learn about how genetics can contribute to our understanding of psychiatric phenotypes.

Difficulty level: Beginner
Duration: 55:15
Speaker: : Sven Cichon

This lesson gives an introductory presentation on how data science can help with scientific reproducibility.

Difficulty level: Beginner
Duration:
Speaker: : Michel Dumontier

This lesson discusses FAIR principles and methods currently in development for assessing FAIRness.

Difficulty level: Beginner
Duration:
Speaker: : Michel Dumontier

In this lesson, you will hear about the current challenges regarding data management, as well as policies and resources aimed to address them. 

Difficulty level: Beginner
Duration: 18:13
Speaker: : Mojib Javadi

The lecture provides an overview of the core skills and practical solutions required to practice reproducible research.

Difficulty level: Beginner
Duration: 1:25:17
Speaker: : Fernando Perez

This lecture covers multiple aspects of FAIR neuroscience data: what makes it unique, the challenges to making it FAIR, the importance of overcoming these challenges, and how data governance comes into play.

Difficulty level: Beginner
Duration: 14:56
Speaker: : Damian Eke