The probability of a hypothesis, given data.

Why math is useful in data science.

Why statistics are useful for data science.

Statistics is exploring data.

Graphical data exploration

Numerical data exploration

Simple description of statistical data.

Basics of hypothesis testing.

Enabling neuroscience research using high performance computing

This lecture covers an introduction to neuroinformatics and its subfields, the content of the short course and future neuroinformatics applications.

Introduction to reproducible research. The lecture provides an overview of the core skills and practical solutions required to practice reproducible research. This lecture was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

This lecture was part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

This lecture was part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Introduction to the Mathematics chapter of Datalabcc's "Foundations in Data Science" series.

Primer on elementary algebra

Primer on linear algebra

Primer on systems of linear equations

Primer on calculus

How calculus relates to optimization

Big O notation