Acerca de este Programa Especializado
Cursos 100 % en línea

Cursos 100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Cronograma flexible

Cronograma flexible

Establece y mantén fechas de entrega flexibles.
Nivel intermedio

Nivel intermedio

Horas para completar

Aprox. 6 meses para completar

Sugerido 7 horas/semana
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English), Coreano...

Habilidades que obtendrás

Software-Defined NetworkingDistributed ComputingBig DataCloud Computing
Cursos 100 % en línea

Cursos 100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Cronograma flexible

Cronograma flexible

Establece y mantén fechas de entrega flexibles.
Nivel intermedio

Nivel intermedio

Horas para completar

Aprox. 6 meses para completar

Sugerido 7 horas/semana
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English), Coreano...

Cómo funciona Programa Especializado

Toma cursos

Un programa especializado de Coursera es un conjunto de cursos que te ayudan a dominar una aptitud. Para comenzar, inscríbete en el programa especializado directamente o échale un vistazo a sus cursos y elige uno con el que te gustaría comenzar. Al suscribirte a un curso que forme parte de un programa especializado, quedarás suscrito de manera automática al programa especializado completo. Puedes completar solo un curso: puedes pausar tu aprendizaje o cancelar tu suscripción en cualquier momento. Visita el panel principal del estudiante para realizar un seguimiento de tus inscripciones a cursos y tu progreso.

Proyecto práctico

Cada programa especializado incluye un proyecto práctico. Necesitarás completar correctamente el proyecto para completar el programa especializado y obtener tu certificado. Si el programa especializado incluye un curso separado para el proyecto práctico, necesitarás completar cada uno de los otros cursos antes de poder comenzarlo.

Obtén un certificado

Cuando completes todos los cursos y el proyecto práctico, obtendrás un Certificado que puedes compartir con posibles empleadores y tu red profesional.

how it works

Hay 6 cursos en este Programa Especializado

Curso1

Cloud Computing Concepts, Part 1

4.5
605 calificaciones
155 revisiones
Cloud computing systems today, whether open-source or used inside companies, are built using a common set of core techniques, algorithms, and design philosophies – all centered around distributed systems. Learn about such fundamental distributed computing "concepts" for cloud computing. Some of these concepts include: clouds, MapReduce, key-value/NoSQL stores, classical distributed algorithms, widely-used distributed algorithms, scalability, trending areas, and much, much more! Know how these systems work from the inside out. Get your hands dirty using these concepts with provided homework exercises. In the programming assignments, implement some of these concepts in template code (programs) provided in the C++ programming language. Prior experience with C++ is required. The course also features interviews with leading researchers and managers, from both industry and academia....
Curso2

Cloud Computing Concepts: Part 2

4.6
190 calificaciones
40 revisiones
Cloud computing systems today, whether open-source or used inside companies, are built using a common set of core techniques, algorithms, and design philosophies – all centered around distributed systems. Learn about such fundamental distributed computing "concepts" for cloud computing. Some of these concepts include: clouds, MapReduce, key-value/NoSQL stores, classical distributed algorithms, widely-used distributed algorithms, scalability, trending areas, and much, much more! Know how these systems work from the inside out. Get your hands dirty using these concepts with provided homework exercises. In the programming assignments, implement some of these concepts in template code (programs) provided in the C++ programming language. Prior experience with C++ is required. The course also features interviews with leading researchers and managers, from both industry and academia. This course builds on the material covered in the Cloud Computing Concepts, Part 1 course....
Curso3

Cloud Computing Applications, Part 1: Cloud Systems and Infrastructure

4.1
316 calificaciones
84 revisiones
Welcome to the Cloud Computing Applications course, the first part of a two-course series designed to give you a comprehensive view on the world of Cloud Computing and Big Data! In this first course we cover a multitude of technologies that comprise the modern concept of cloud computing. Cloud computing is an information technology revolution that has just started to impact many enterprise computing systems in major ways, and it will change the face of computing in the years to come. We start the first week by introducing some major concepts in cloud computing, the economics foundations of it and we introduce the concept of big data. We also cover the concept of software defined architectures, and how virtualization results in cloud infrastructure and how cloud service providers organize their offerings. In week two, we cover virtualization and containers with deeper focus, including lectures on Docker, JVM and Kubernates. We finish up week two by comparing the infrastructure as a service offering by the big three: Amazon, Google and Microsoft. Week three moves to higher level of cloud offering, including platform as a service, mobile backend as a service and even serverless architectures. We also talk about some of the cloud middleware technologies that are fundamental to cloud based applications such as RPC and REST, JSON and load balancing. Week three also covers metal as a service (MaaS), where physical machines are provisioned in a cloud environment. Week four introduces higher level cloud services with special focus on cloud storage services. We introduce Hive, HDFS and Ceph as pure Big Data Storage and file systems, and move on to cloud object storage systems, virtual hard drives and virtual archival storage options. As discussion on Dropbox cloud solution wraps up week 4 and the course....
Curso4

Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud

4.1
157 calificaciones
29 revisiones
Welcome to the Cloud Computing Applications course, the second part of a two-course series designed to give you a comprehensive view on the world of Cloud Computing and Big Data! In this second course we continue Cloud Computing Applications by exploring how the Cloud opens up data analytics of huge volumes of data that are static or streamed at high velocity and represent an enormous variety of information. Cloud applications and data analytics represent a disruptive change in the ways that society is informed by, and uses information. We start the first week by introducing some major systems for data analysis including Spark and the major frameworks and distributions of analytics applications including Hortonworks, Cloudera, and MapR. By the middle of week one we introduce the HDFS distributed and robust file system that is used in many applications like Hadoop and finish week one by exploring the powerful MapReduce programming model and how distributed operating systems like YARN and Mesos support a flexible and scalable environment for Big Data analytics. In week two, our course introduces large scale data storage and the difficulties and problems of consensus in enormous stores that use quantities of processors, memories and disks. We discuss eventual consistency, ACID, and BASE and the consensus algorithms used in data centers including Paxos and Zookeeper. Our course presents Distributed Key-Value Stores and in memory databases like Redis used in data centers for performance. Next we present NOSQL Databases. We visit HBase, the scalable, low latency database that supports database operations in applications that use Hadoop. Then again we show how Spark SQL can program SQL queries on huge data. We finish up week two with a presentation on Distributed Publish/Subscribe systems using Kafka, a distributed log messaging system that is finding wide use in connecting Big Data and streaming applications together to form complex systems. Week three moves to fast data real-time streaming and introduces Storm technology that is used widely in industries such as Yahoo. We continue with Spark Streaming, Lambda and Kappa architectures, and a presentation of the Streaming Ecosystem. Week four focuses on Graph Processing, Machine Learning, and Deep Learning. We introduce the ideas of graph processing and present Pregel, Giraph, and Spark GraphX. Then we move to machine learning with examples from Mahout and Spark. Kmeans, Naive Bayes, and fpm are given as examples. Spark ML and Mllib continue the theme of programmability and application construction. The last topic we cover in week four introduces Deep Learning technologies including Theano, Tensor Flow, CNTK, MXnet, and Caffe on Spark....

Instructores

Avatar

Reza Farivar

Data Engineering Manager at Capital One, Adjunct Research Assistant Professor of Computer Science
Department of Computer Science
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Ankit Singla

Assistant Professor
Department of Computer Science, ETH Zürich
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Indranil Gupta

Professor
Department of Computer Science
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P. Brighten Godfrey

Associate Professor
Department of Computer Science
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Roy H. Campbell

Professor of Computer Science
Department of Computer Science
Graduation Cap

Comienza a trabajar para obtener tu maestría

Este programa especializado es parte del Master in Computer Science completamente en línea de University of Illinois at Urbana-Champaign. Si eres aceptado en el programa completo, tus cursos cuentan para tu título.

Acerca de University of Illinois at Urbana-Champaign

The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs. ...

Preguntas Frecuentes

  • ¡Sí! Para empezar, haz clic en la tarjeta del curso que te interesa e inscríbete. Puedes inscribirte y completar el curso para obtener un certificado que puedes compartir o puedes acceder al curso como oyente para ver los materiales del curso de manera gratuita. Cuando cancelas la suscripción de un curso que forma parte de un programa especializado, se cancela automáticamente la suscripción de todo el programa especializado. Visita el panel del estudiante para realizar un seguimiento de tu progreso.

  • Este curso es completamente en línea, de modo que no necesitas ir a un aula en persona. Puedes acceder a tus lecciones, lecturas y tareas en cualquier momento y cualquier lugar a través de Internet o tu dispositivo móvil.

  • Este programa especializado no otorga crédito universitario, pero algunas universidades pueden aceptar los Certificados del programa especializado para el crédito. Consulta con tu institución para obtener más información.

  • Time to completion can vary widely based on your schedule. Most learners are able to complete the Specialization in 4-5 months.

  • Each course in the Specialization is offered on a regular schedule with sessions starting about once per month. If you don't complete a course on the first try, you can easily transfer to the next session, and your completed work and grades will carry over.

  • Basic working knowledge of computers and computer systems

    Familiarity with common programming languages (e.g., C, C++, Java)

  • It is recommended that the courses in the Specialization be taken in the order outlined. In the Capstone Project, you will have the opportunity to synthesize your learning in all the courses and apply your combined skills in a final project.

  • There will be hands-on laboratory experiments (Load Balancing and Web Services, MapReduce, Hive, Storm, and Mahout). Case studies will be drawn from Yahoo, Google, Twitter, Facebook, data mining, analytics, and machine learning. We will also explore current practice by talking to leading industry experts, as well as looking into interesting new research that might shape the cloud network’s future.

¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.