E.g., Monday, February 8, 2016
E.g., Monday, February 8, 2016
E.g., Monday, February 8, 2016
Jan 18th 2016

An introduction to the statistics behind the most popular genomic data science projects. This is the sixth course in the Genomic Big Data Science Specialization from Johns Hopkins University.

Average: 8.3 (3 votes)
Self Paced

Investigate, Visualize, and Summarize Data Using R.

Average: 3.8 (8 votes)
Self Paced

The purpose of this course is to introduce you to the subject of statistics as a science of data. There is data abound in this information age; how to extract useful knowledge and gain a sound understanding in complex data sets has been more of a challenge. In this course, we will focus on the fundamentals of statistics, which may be broadly described as the techniques to collect, clarify, summarize, organize, analyze, and interpret numerical information.

Average: 4.7 (6 votes)
Self Paced

Statistics is about extracting meaning from data. In this class, we will introduce techniques for visualizing relationships in data and systematic techniques for understanding the relationships using mathematics.

Average: 3.1 (8 votes)
Self Paced

This course follows on from FE & RM Part I. We will consider portfolio optimization, risk management and some advanced examples of derivatives pricing that draw from structured credit, real options and energy derivatives. We will also cast a critical eye on how financial models are used in practice.

Average: 10 (2 votes)
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.

No votes yet
Self Paced

Learn what it takes to become a data scientist.

Average: 7 (1 vote)
Self Paced

This course will introduce you to the fundamentals of probability theory and random processes. The theory of probability was originally developed in the 17th century by two great French mathematicians, Blaise Pascal and Pierre de Fermat, to understand gambling.

No votes yet
Self Paced

This course will introduce you to business statistics, or the application of statistics in the workplace.Statistics is a course in the methods for gathering, analyzing, and interpreting data.

Average: 3 (2 votes)
To be announced

En este curso presentaremos los contenidos fundamentales sobre Estadística descriptiva.

No votes yet
Oct 1st 2015

This course will introduce students to the major concepts and tools for collecting, analyzing and drawing conclusions from data.

No votes yet
Feb 2nd 2016

An introduction to probabilistic models, including random processes and the basic elements of statistical inference.

Average: 8 (1 vote)
Mar 22nd 2016

Use R to learn the fundamental statistical topic of basic inferential statistics.

No votes yet
Mar 1st 2016

L'objectif de ce cours est de comprendre et appliquer les quatre méthodes fondamentales de l'analyse des données : analyse en composantes principales, analyse factorielle des correspondances, analyse des correspondances multiples et classification ascendante hiérarchique.

Average: 10 (1 vote)
Feb 22nd 2016

Regression modeling is the standard method for analysis of continuous response data. This course provides theoretical and practical training in statistical modeling with particular emphasis on linear and multiple regression.

No votes yet
Jan 12th 2016

This is an introductory-level course in supervised learning, with a focus on regression and classification methods. The syllabus includes: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines. Some unsupervised learning methods are discussed: principal components and clustering (k-means and hierarchical).

Average: 9.3 (6 votes)
Self Paced Course - Start anytime

En este curso de Probabilidad y Estadística estudiamos dos áreas fundamentales del conocimiento: La Probabilidad como una rama de las matemáticas que mide cuantitativamente la posibilidad de que un experimento produzca un determinado resultado, y la Estadística como ciencia formal que estudia la recolección, análisis e interpretación de datos de una muestra.

No votes yet
Jan 25th 2016

Our world is rich with data sources, and technology makes data more accessible than ever before! To help ensure students are future ready to use data for making informed decisions, many countries around the world have increased the emphasis on statistics and data analysis in school curriculum–from elementary/primary grades through college. This course allows you to learn, along with colleagues from other schools, an investigation cycle to teach statistics and to help students explore data to make evidence-based claims.

No votes yet
Jan 25th 2016

En vous proposant une initiation rigoureuse aux principes de base de la méthodologie des sondages, ce MOOC vous aidera à vous forger un regard plus critique et avisé sur les statistiques qui inondent notre quotidien.

No votes yet
Feb 2nd 2016

Use R to learn fundamental statistical topics such as descriptive statistics and modeling.

Average: 8 (1 vote)

Pages

 

Tell your friends: