Lessons

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Theory of network dynamics
Course:
Introduction to computational neuroscience

Spiking neuron networks and linear response models.

Difficulty level: Beginner
Duration: 1:24:22
Speaker: : Tatjana Tchumatchenko
Neural data analysis: The Bayesics
Course:
Introduction to computational neuroscience

Bayesian neuron models and parameter estimation.

Difficulty level: Beginner
Duration: 1:12:38
Speaker: : Jakob Macke
Bayesian models of perception, cognition and learning
Course:
Introduction to computational neuroscience

Bayesian memory and learning, how to go from observations to latent variables.

Difficulty level: Beginner
Duration: 1:33:34
Speaker: : Máté Lengyel
Constraints on information processing
Course:
Introduction to computational neuroscience

Constraints can help us understand how the brain works.

Difficulty level: Beginner
Duration: 1:34:42
Speaker: : Simon Laughlin
Evolution and Brain Computation
Course:
Introduction to computational neuroscience

Approaching neural systems from an evolutionary perspective

Difficulty level: Beginner
Duration: 1:29:38
Speaker: : Gilles Laurent
Mathematics: Bayes' theorem
Course:
Foundations of Data Science

The probability of a hypothesis, given data.

Difficulty level: Beginner
Duration: 7:57
Speaker: : Barton Poulson
Mathematics: Next steps
Course:
Foundations of Data Science

Why math is useful in data science.

Difficulty level: Beginner
Duration: 1:35
Speaker: : Barton Poulson
Statistics (intro)
Course:
Foundations of Data Science

Why statistics are useful for data science.

Difficulty level: Beginner
Duration: 4:01
Speaker: : Barton Poulson
Statistics: Exploration overview
Course:
Foundations of Data Science

Statistics is exploring data.

Difficulty level: Beginner
Duration: 2:23
Speaker: : Barton Poulson
Statistics: Exploratory graphics
Course:
Foundations of Data Science

Graphical data exploration

Difficulty level: Beginner
Duration: 8:01
Speaker: : Barton Poulson
Statistics: Exploratory statistics
Course:
Foundations of Data Science

Numerical data exploration

Difficulty level: Beginner
Duration: 5:05
Speaker: : Barton Poulson
Statistics: Descriptive statistics
Course:
Foundations of Data Science

Simple description of statistical data.

Difficulty level: Beginner
Duration: 10:16
Speaker: : Barton Poulson
Statistics: Hypothesis Testing
Course:
Foundations of Data Science

Basics of hypothesis testing.

Difficulty level: Beginner
Duration: 06:04
Speaker: : Barton Poulson
Statistics: Inferential statistics
Course:
Foundations of Data Science

Inferring results from incomplete data

Difficulty level: Beginner
Duration: 4:28
Speaker: : Barton Poulson
Statistics: Estimation
Course:
Foundations of Data Science

Finding parameter values, confidence intervals.

Difficulty level: Beginner
Duration: 08:04
Speaker: : Barton Poulson
Statistics: Estimators
Course:
Foundations of Data Science

Methods for estimating parameters.

Difficulty level: Beginner
Duration: 5:29
Speaker: : Barton Poulson
Statistics: Measures of fit
Course:
Foundations of Data Science

Measuring the correspondece between data and model.

Difficulty level: Beginner
Duration: 3:30
Speaker: : Barton Poulson
Statistics: Feature selection
Course:
Foundations of Data Science

How to choose useful variables.

Difficulty level: Beginner
Duration: 6:15
Speaker: : Barton Poulson
Statistics: Problems in modelling
Course:
Foundations of Data Science

Common problems in statistical modelling.

Difficulty level: Beginner
Duration: 5:58
Speaker: : Barton Poulson
Statistics: Model validation
Course:
Foundations of Data Science

Common problems in statistical modelling.

Difficulty level: Beginner
Duration: 3:50
Speaker: : Barton Poulson

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