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.

Inferring results from incomplete data

Finding parameter values, confidence intervals.

Methods for estimating parameters.

Measuring the correspondece between data and model.

How to choose useful variables.

Common problems in statistical modelling.

Common problems in statistical modelling.

You don't have to be a wizard to do statistics!

Overview of possible follow up courses and subjects from the same publisher.

In an overview of the structure of the mammalian neocortex, this lecture explains how the mammalian cortex is organized in a hierarchy, describing the columnar principle and canonical microcircuits

The retina has 60 different types of neurons. What are their functions? This lecture explores the definition of cell types and their functions in the mammalian retina.

Optical imaging offers a look inside the working brain. This lecture takes a look at orientation and ocular dominance columns in the visual cortex, and shows how they can be viewed with calcium imaging.

This lecture explains these ideas and explores the task of characterizing neuronal response properties using information theory.

How does the brain learn? This lecture discusses the roles of development and adult plasticity in shaping functional connectivity.