This talk introduces Bayes' theorem, which describes the probability of an event, based on prior knowledge of conditions that might be related to the event.
This lesson recaps why math, in a number of ways, is extremely useful in data science.
This lesson provides an introduction to the lessons in this course that deal with statistics and why they are useful for data science.
In this lesson, users will learn about the importance of exploratory analysis, as well as how statistics enables one to become familiar with and understand one's data.
This lesson goes over graphical data exploration, including motivations for its use as well as practical examples of visualizing data distributions.
In this lesson, users learn about exploratory statistics, and are introduced to various methods for numerical data exploration.
This lesson overview some simple descriptions of statistical data.
This lesson covers the basics of hypothesis testing.
This lesson describes the Neuroscience Gateway , which facilitates access and use of National Science Foundation High Performance Computing resources by neuroscientists.
This lesson gives an introduction to high-performance computing with the Compute Canada network, first providing an overview of use cases for HPC and then a hands-on tutorial. Though some examples might seem specific to the Calcul Québec, all computing clusters in the Compute Canada network share the same software modules and environments.
This lesson provides a short overview of the main features of the Canadian Open Neuroscience Platform (CONP) Portal, a web interface that facilitates open science for the neuroscience community by simplifying global access to and sharing of datasets and tools. The Portal internalizes the typical cycle of a research project, beginning with data acquisition, followed by data processing with published tools, and ultimately the publication of results with a link to the original dataset.
This talk presents an overview of CBRAIN, a web-based platform that allows neuroscientists to perform computationally intensive data analyses by connecting them to high-performance computing facilities across Canada and around the world.
This lecture provides an introductory overview of some of the most important concepts in software engineering.
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.
This is the second of three lectures around current challenges and opportunities facing neuroinformatic infrastructure for handling sensitive data.
In this lesson you will learn about current efforts towards integrating multimodal human brain data using the open source SCORE HED library schema.
This lecture will highlight our current understanding and recent developments in the field of neurodegenerative disease research, as well as the future of diagnostics and treatment of neurodegenerative diseases.
This lecture continues from part one (previous lesson), highlighting our current understanding and recent developments in the field of neurodegenerative disease research, as well as the future of diagnostics and treatment of neurodegenerative diseases.
This lecture picks up from the previous lesson, providing an overview of neuroimaging techniques and their clinical applications.
This lesson provides a basic introduction to clinical presentation of schizophrenia, its etiology, and current treatment options.