Resumo do curso

The world is trending in real time! Learn from Twitter to scalably process tweets, or any big data stream, in real-time to drive d3 visualizations using Apache Storm, the “Hadoop of Real Time.” Storm is free, open source, and fun to use! Learn from Karthik Ramasamy, Technical Lead of Storm@Twitter, about the distributed, fault-tolerant, and flexible technology used to power Twitter’s real-time data flow pipeline. Twitter open sourced Storm in 2011, and it graduated to a top-level Apache project in September, 2014.

Starting from basic distributed concepts presented during our first Udacity-Twitter Storm Hackathon, link Storm concepts to Storm syntax to scalably drive Word Cloud visualizations with Vagrant, Ubuntu, Maven, Flask, Redis, and d3. Link to the public Twitter gardenhose stream to process live tweets, parse embedded URLs, and calculate Top worldwide hashtags. Extend beyond Storm basics by exploring multi-language capabilities in Python, integrate open source components, and implement real-time streaming joins.

In your final project, follow real-time trending topics by implementing the data pipeline to visualize only tweets that contain Top worldwide hashtags. Extend your project by exploring the Twitter API, or any data source, alongside Hackathon participants as they design their own ideas, receive feedback from Karthik, and open source a final project calculating real-time tweet sentiment and geolocation to drive a U.S. Map.

Valor do curso
Grátis
Tempo estimado Tempo total entre hoje e dia da formatura depende do seu compromisso semanal. Em média, os nossos graduados completam este nanodegree em 2 semanas
2 semanas
Nível
intermediário
O curso inclui

Videoaulas

Testes interativos

Aulas com profissionais do setor

Ritmo individual de aprendizado

Comunidade de apoio aos alunos

Sua jornada de aprendizagem

Este curso aberto é seu primeiro passo em direção a uma nova carreira com o programa Engenheiro de Machine Learning

Curso Aberto

Real-Time Analytics with Apache Storm

por Twitter

Enhance your skill set and boost your hirability through innovative, independent learning.

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Karthik Ramasamy
Karthik Ramasamy

Instrutor

Lewis Kaneshiro
Lewis Kaneshiro

Instrutor

Pré-requisitos

Programming language required: Java

To be successful, you'll need intermediate knowledge of Java. Specifically, this is defined by experience and comfort with Java syntax, compile & run-time error diagnostics and debugging, ability to use javadocs as needed, and intermediate data structures including Arrays, HashMaps, and LinkedLists.

No prior experience is assumed in Ubuntu, git, Maven, Redis, Flask (Python) or d3 (Javascript). Python is useful, but optional. A basic course such as CS101 or OO in Python would be helpful.

Por que fazer este curso?

Learn by doing! The world is going real time. Batch processing, popularized by Hadoop, has latency exceeding required real-time demands of modern mobile, connected, always-on users. Stream processing with seconds-required response time is necessary to meet this demand. Twitter is a world leader in real-time processing at scale. Learn the future from the company defining it.

Quais são os recursos?
Vídeos dos instrutores Exercícios práticos Aulas com profissionais do setor