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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

In this lesson, you will learn about hardware for computing for non-ICT specialists.

Difficulty level: Beginner
Duration: 43:21
Speaker: : Steve Furber

This lecture covers the emergence of cognitive science after the Second World War as an interdisciplinary field for studying the mind, with influences from anthropology, cybernetics, and artificial intelligence.

Difficulty level: Beginner
Duration: 51:07

This lecture covers different perspectives on the study of the mental, focusing on the difference between Mind and Brain. 

Difficulty level: Beginner
Duration: 1:16:30

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 brief talk goes into work being done at The Alan Turing Institute to solve real-world challenges and democratize computer vision methods to support interdisciplinary and international researchers. 

Difficulty level: Beginner
Duration: 7:10

This lesson is the first part of a three-part series on the development of neuroinformatic infrastructure to ensure compliance with European data privacy standards and laws. 

Difficulty level: Beginner
Duration: 1:10:05
Speaker: : Michael Schirner

This is the second of three lectures around current challenges and opportunities facing neuroinformatic infrastructure for handling sensitive data. 

Difficulty level: Beginner
Duration: 48:26
Speaker: : Michael Schirner

This lesson contains the first part of the lecture Data Science and Reproducibility. You will learn about the development of data science and what the term currently encompasses, as well as how neuroscience and data science intersect. 

Difficulty level: Beginner
Duration: 32:18
Speaker: : Ariel Rokem

This lesson aims to define computational neuroscience in general terms, while providing specific examples of highly successful computational neuroscience projects. 

Difficulty level: Beginner
Duration: 59:21
Speaker: : Alla Borisyuk

This lecture gives a tour of what neuroethics is and how it applies to neuroscience and neurotechnology, while also addressing justice concerns within both fields. 

Difficulty level: Beginner
Duration: 58:45
Speaker: : Tim Brown

Computer arithmetic is necessarily performed using approximations to the real numbers they are intended to represent, and consequently it is possible for the discrepancies between the actual solution and the approximate solutions to diverge, i.e. to become increasingly different. This lecture focuses on how this happens and techniques for reducing the effects of these phenomena and discuss systems which are chaotic.

Difficulty level: Beginner
Duration: 36:56
Speaker: : David Lester

This lecture will addresses what it means for a problem to have a computable solution, methods for combining computability results to analyse more complicated problems, and finally look in detail at one particular problem which has no computable solution: the halting problem.

Difficulty level: Beginner
Duration: 28:28
Speaker: : David Lester

This lecture focuses on computational complexity, a concept which lies at the heart of computer science thinking. In short, it is a way to quickly gauge an approximation to the computational resource required to perform a task.

Difficulty level: Beginner
Duration: 27:33
Speaker: : David Lester
Course:

This lecture gives an introduction to simulation, models, and the neural simulation tool NEST. 

Difficulty level: Beginner
Duration: 1:48:18
Course:

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

Difficulty level: Beginner
Duration: 1:23:01
Speaker: : Gaute Einevoll

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

This lesson provides an introduction to neurons, synaptic transmission, and ion channels.

Difficulty level: Beginner
Duration: 46:07

This lecture consists of the second half of the introduction to signal transduction, here focusing on cell receptors and signalling cascades.

Difficulty level: Beginner
Duration: 41:38