E-Learning-Inclusivo (Mashup)

What else can we predict? In theory, any event that is not random, provided we have enough data to model the context. Examples include passenger load in public transports, availability of parking spots, traffic jams, waste production, energy consumption and revenues of a shop in a specific street. These all share a common underlying principle: use context rather than history to predict behavior.

In themselves, each of these predictions could lead to amazing new products and services. The real power though comes from integrating everything together and modeling an entire city and its interactions with people. For instance, if you can predict where people will need to go tomorrow, then you can create optimal bus routes, minimizing time to destination and walking distance, taking into account predicted traffic, weather and garbage collection schedules. In this ideal system, all services would be optimal and available to citizens at anytime. We call this new way of designing cities "Algorithmic Urbanism".

Here’s an updated version of our Big Data Investment Map. I’ve collected information about ca. 50 of the most important Big Data startups via the Crunchbase API. The funding rounds were used to create a weighted directed network with investments being the edges between the nodes (investors and/or startups). If there were multiple companies or persons participating in a funding round, I split the sum between all investors.

Imagining the Future City: London 2062 (free download) is an edited collection based on the London 2062 project from UCL’s Grand Challenge of Sustainable Cities. The London 2062 project engaged academics, policy makers and practitioners, providing a forum for serious debate about the challenges and opportunities for London in the five decades following the Olympics.

The book is divided into four sections, considering London in terms of Things, Connections, Powerand Dreams. The book features contributions from leading academic thinkers at UCL and from those involved in shaping London on the ground, through policy and practice. The authors consider the future of London from multiple viewpoints, including transport, energy, smart infrastructure, water, population, housing and the economy.

The aim of this book, and the London 2062 programme, is to open discussion about the future of London. What is the future we want to see for London? Which priorities for a global city are in opposition? How can we meet carbon emission targets and deliver new infrastructure in the 21st Century?

LONDON CALLING - How will you influence the shape of your city get involved folks! Thank you @plevy

A lot has been written about the ways that big data has changed scientific enquiry, but as supercomputers increase in power and the tools to use them become less obtuse, whole new academic disciplines are beginning to feel the benefits of crunching data.

Believe it or not, some people even think we can forecast the future with big data. Predicting world-changing events is a possibility, some claim, if you treat society and history like a big data problem. It's how big data analyst Kalev Leetaru found where Osama bin Laden had been hiding, in a way.

Literally a list of 100 data innovations. I particularly like IBM's content analysis of ingredients and cooking methods to create new and exotic recipes.

El Analista de Datos, de grandes volúmenes de datos, se ha convertido ya en uno de los perfiles profesionales que más futuro ofrecen en el nuevo mundo del BigData.

Y es un perfil nétamente "informático" en su vertiente más matemática / estadística, pero con profundos conocimientos de programación en Python, Hadoop, MapReduce, el clásico SQL, o el nuevo lenguaje R.

Por ello, no ha que dejar de mirar los nuevos cursos de formación online en BigData que vienen de las mejores universidades del mundo, entre ellos los que ofrecen en Piazza, Coursera o Udacity :

- https://piazza.com/#fall2013/cs109

- https://www.coursera.org/course/compdata (empieza el 6 de enero de 2014)

- https://www.udacity.com/course/ud359 (empieza en enero de 2014. Aunque los cursos de Udacity ya no son grautitos, tampoco son caros: este cuesta 105$/mes, y dura 2 meses, y si la calidad es igual que los que he realizado con ellos, es un dinero muuuy bien invertido)

Pero tampoco hay que dejar de lado a la oferta online de las universidades españolas, que algunas ya ofrecen cursos en MOOC, aunque cesconozco si hay en el tema del Bigdata.

Para más datos, mira en este post antiguo:

http://sco.lt/6CJoMj