This course covers the design, acquisition, and analysis of Functional Magnetic Resonance Imaging (fMRI) data.

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Dec 5th 2016

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In this course you will learn a whole lot of modern physics (classical and quantum) from basic computer programs that you will download, generalize, or write from scratch, discuss, and then hand in. Join in if you are curious (but not necessarily knowledgeable) about algorithms, and about the deep insights into science that you can obtain by the algorithmic approach.

Syllabus

Week 1: Monte Carlo algorithms (Direct sampling, Markov-chain sampling)

Week 2: Hard disks: From Classical Mechanics to Statistical Mechanics

Week 3: Entropic interactions and phase transitions

Week 4: Sampling and integration

Week 5: Density matrices and Path integrals (Quantum Statistical mechanics 1/3)

Week 6: Lévy Quantum Paths (Quantum Statistical mechanics 2/3)

Week 7: Bose-Einstein condensation (Quantum Statistical mechanics 3/3)

Week 8: Ising model - Enumerations and Monte Carlo algorithms

Week 9: Dynamic Monte Carlo, simulated annealing

Week 10: The Alpha and the Omega of Monte Carlo, Review, Party

Nov 21st 2016

This course covers the design, acquisition, and analysis of Functional Magnetic Resonance Imaging (fMRI) data.

Dec 5th 2016

Understanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. This course will also prepare you for the next course in the specialization - the course Inferential Statistics.

Dec 5th 2016

This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization.

Dec 5th 2016

A data product is the production output from a statistical analysis. Data products automate complex analysis tasks or use technology to expand the utility of a data informed model, algorithm or inference. This course covers the basics of creating data products using Shiny, R packages, and interactive graphics. The course will focus on the statistical fundamentals of creating a data product that can be used to tell a story about data to a mass audience.

Nov 21st 2016

We are always using experiments to improve our lives, our community, and our work. Are you doing it efficiently? Or are you (incorrectly) changing one thing at a time and hoping for the best? In this course, you will learn how to plan efficient experiments - testing with many variables. Our goal is to find the best results using only a few experiments. A key part of the course is how to optimize a system.

Self Paced

A matemática é a ciência do raciocínio lógico e abstrato, estuda quantidades, medidas, espaços, estruturas e variações. Um trabalho matemático consiste em procurar por padrões, formular conjecturas e, por meio de deduções rigorosas a partir de axiomas e definições, estabelecer novos resultados.

Nov 7th 2016

Il corso copre la matematica di base, permettendo di colmare eventuali lacune e di mettere a punto la preparazione necessaria all'ingresso all'università.

The course covers the fundamentals of Math, thus allowing to fill high school gaps and to optimize students’ knowledge as they start college.

Nov 14th 2016

This course aims to help you to draw better statistical inferences from empirical research. First, we will discuss how to correctly interpret p-values, effect sizes, confidence intervals, Bayes Factors, and likelihood ratios, and how these statistics answer different questions you might be interested in. Then, you will learn how to design experiments where the false positive rate is controlled, and how to decide upon the sample size for your study, for example in order to achieve high statistical power.

Nov 28th 2016

By now you have definitely heard about data science and big data. In this one-week class, we will provide a crash course in what these terms mean and how they play a role in successful organizations. This class is for anyone who wants to learn what all the data science action is about, including those who will eventually need to manage data scientists. The goal is to get you up to speed as quickly as possible on data science without all the fluff. We've designed this course to be as convenient as possible without sacrificing any of the essentials.

Dec 5th 2016

Inferential statistics are concerned with making inferences based on relations found in the sample, to relations in the population. Inferential statistics help us decide, for example, whether the differences between groups that we see in our data are strong enough to provide support for our hypothesis that group differences exist in general, in the entire population.

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Self-Paced MOOCs

MOOC List Coupon Discount

Providers and Categories

University / Entity

Instructor

Country

Language

Type of Certificate

Tag

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- MOOC stands for a Massive Open Online Course.
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