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.
This lecture covers structured data, databases, federating neuroscience-relevant databases, ontologies.
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
Basics of probability.
2nd part of the lecture. Introduction to cell receptors and signalling cascades
GABAergic interneurons and local inhibition on the circuit level.
The ionic basis of the action potential, including the Hodgkin Huxley model.