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This lecture provides an introductory overview of some of the most important concepts in software engineering.

Difficulty level: Beginner
Duration: 32:59
Speaker: : Jeff Muller

In this lesson, you will learn in more detail about neuromorphic computing, that is, non-standard computational architectures that mimic some aspect of the way the brain works. 

Difficulty level: Intermediate
Duration: 10:08
Speaker: : Dan Goodman

This video provides a very quick introduction to some of the neuromorphic sensing devices, and how they offer unique, low-power applications.

Difficulty level: Intermediate
Duration: 2:37
Speaker: : Dan Goodman

This lesson describes the fundamentals of genomics, from central dogma to design and implementation of GWAS, to the computation, analysis, and interpretation of polygenic risk scores. 

Difficulty level: Intermediate
Duration: 1:28:16
Speaker: : Dan Felsky

This lesson provides an overview of the database of Genotypes and Phenotypes (dbGaP), which was developed to archive and distribute the data and results from studies that have investigated the interaction of genotype and phenotype in humans.

Difficulty level: Beginner
Duration: 48:22
Speaker: : Michael Feolo

This lecture provides an introduction to optogenetics, a biological technique to control the activity of neurons or other cell types with light.

Difficulty level: Beginner
Duration: 39:34
Speaker: : Adam Packer

This primer on optogenetics primer discusses how to manipulate neuronal populations with light at millisecond resolution and offers possible applications such as curing the blind and "playing the piano" with cortical neurons.

Difficulty level: Beginner
Duration: 59:06
Speaker: : Clay Reid

This lesson gives an introduction to the Mathematics chapter of Datalabcc's Foundations in Data Science series.

Difficulty level: Beginner
Duration: 2:53
Speaker: : Barton Poulson

This lesson serves a primer on elementary algebra.

Difficulty level: Beginner
Duration: 3:03
Speaker: : Barton Poulson

This lesson provides a primer on linear algebra, aiming to demonstrate how such operations are fundamental to many data science. 

Difficulty level: Beginner
Duration: 5:38
Speaker: : Barton Poulson

In this lesson, users will learn about linear equation systems, as well as follow along some practical use cases.

Difficulty level: Beginner
Duration: 5:24
Speaker: : Barton Poulson

This talk gives a primer on calculus, emphasizing its role in data science.

Difficulty level: Beginner
Duration: 4:17
Speaker: : Barton Poulson

This lesson clarifies how calculus relates to optimization in a data science context. 

Difficulty level: Beginner
Duration: 8:43
Speaker: : Barton Poulson

This lesson covers Big O notation, a mathematical notation that describes the limiting behavior of a function as it tends towards a certain value or infinity, proving useful for data scientists who want to evaluate their algorithms' efficiency.

Difficulty level: Beginner
Duration: 5:19
Speaker: : Barton Poulson

This lesson serves as a primer on the fundamental concepts underlying probability. 

Difficulty level: Beginner
Duration: 7:33
Speaker: : Barton Poulson

Serving as good refresher, this lesson explains the maths and logic concepts that are important for programmers to understand, including sets, propositional logic, conditional statements, and more.

This compilation is courtesy of freeCodeCamp.

Difficulty level: Beginner
Duration: 1:00:07
Speaker: : Shawn Grooms

This lesson provides a useful refresher which will facilitate the use of Matlab, Octave, and various matrix-manipulation and machine-learning software.

This lesson was created by RootMath.

Difficulty level: Beginner
Duration: 1:21:30
Speaker: :

This lesson breaks down the principles of Bayesian inference and how it relates to cognitive processes and functions like learning and perception. It is then explained how cognitive models can be built using Bayesian statistics in order to investigate how our brains interface with their environment. 

This lesson corresponds to slides 1-64 in the PDF below. 

Difficulty level: Intermediate
Duration: 1:28:14

This is a tutorial on designing a Bayesian inference model to map belief trajectories, with emphasis on gaining familiarity with Hierarchical Gaussian Filters (HGFs).

 

This lesson corresponds to slides 65-90 of the PDF below. 

Difficulty level: Intermediate
Duration: 1:15:04
Speaker: : Daniel Hauke

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