• Duración:
    8 semanas
  • Dedicación:
    6–8 horas por semana
  • Precio:

    GRATIS
    Agregar un Certificado Verificado por $750 USD

  • Institución
  • Tema:
  • Nivel:
    Intermediate
  • Idioma:
    English
  • Transcripción de video:
    English
  • Tipo de curso:
    Al ritmo del instructor

Prerrequisitos

Python programming, basic knowledge of probability and statistics

Sobre este curso

Omitir Sobre este curso

This course teaches the principles and practices of big data for improving the reliability and the security of computing systems. Big data is a technology that is changing the way we do business and the way we play. As there is a tremendous growth in data being collected about every process and product in operation, there is value to be mined from this abundance of data. This means that big data is being applied in areas where there is great commercial advantage to be had, and consequently, attacks and failures have become a serious concern.

This course asks and answers the question: Can big data be used to improve the reliability and the security of the processes that we rely on in our work and personal lives? Do big data techniques introduce new vulnerabilities that we should be aware of as we adopt big data practices in so many aspects of our lives? And what kinds of mitigations can be designed and deployed against such vulnerabilities?

The course is taught by a leading researcher in reliability and security and an award-winning teacher.

The course has a practical bent and introduces only the necessary theory and in the context of its application to today’s industrial big data context. The principles are exemplified through popular big data frameworks, such as, Apache Spark and Spark Streaming, Flink, Mesos, and containers.

The course first lays out the problem landscape in the context of upsurge of data and its implications for reliability and for security. Then it describes how we can measure the relevant attributes. Next, it looks at the application-driven requirements and constraints for applying big data for reliability and security. Then it presents how the data can be processed for improving the resilience of the processes that depend on the data. It delves into a set of techniques for defending big data techniques against natural failures (the reliability aspect) and against malicious attacks (the security aspect).

The different aspects are tied together through a set of challenge programming projects that are based on novel datasets that we have collected and curated.

Lo que aprenderás

Omitir Lo que aprenderás
  • Formulate the reliability and the security requirements of a production system
  • Understand and develop big data techniques for improving reliability and security of computing systems
  • Construct software artifacts to instantiate the techniques for real-world datasets and under realistic conditions

Plan de estudios

Omitir Plan de estudios

Conoce a tus instructores

Saurabh Bagchi
Professor, School of Electrical and Computer Engineering and Department of Computer Science
Purdue University

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¿Quién puede hacer este curso?

Lamentablemente, las personas de uno o más de los siguientes países o regiones no podrán registrarse para este curso: Irán, Cuba y la región de Crimea en Ucrania. Si bien edX consiguió licencias de la Oficina de Control de Activos Extranjeros de los EE. UU. (U.S. Office of Foreign Assets Control, OFAC) para ofrecer nuestros cursos a personas en estos países y regiones, las licencias que hemos recibido no son lo suficientemente amplias como para permitirnos dictar este curso en todas las ubicaciones. edX lamenta profundamente que las sanciones estadounidenses impidan que ofrezcamos todos nuestros cursos a cualquier persona, sin importar dónde viva.