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Voltar para Introdução a Big Data

Comentários e feedback de alunos de Introdução a Big Data da instituição Universidade da Califórnia, San Diego

10,675 classificações

Sobre o curso

Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible -- increasing the potential for data to transform our world! At the end of this course, you will be able to: * Describe the Big Data landscape including examples of real world big data problems including the three key sources of Big Data: people, organizations, and sensors. * Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and why each impacts data collection, monitoring, storage, analysis and reporting. * Get value out of Big Data by using a 5-step process to structure your analysis. * Identify what are and what are not big data problems and be able to recast big data problems as data science questions. * Provide an explanation of the architectural components and programming models used for scalable big data analysis. * Summarize the features and value of core Hadoop stack components including the YARN resource and job management system, the HDFS file system and the MapReduce programming model. * Install and run a program using Hadoop! This course is for those new to data science. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Hardware Requirements: (A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size. Software Requirements: This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge. Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+....

Melhores avaliações


11 de ago de 2021

I love the course. It goes deep into the foundations, and then finishes up with an actual lab where you learn by practice. I greatly benefited from it and feel I have achieved a milestone in big data.


8 de set de 2019

I love the course. It goes deep into the foundations, and then finishes up with an actual lab where you learn by practice. I greatly benefited from it and feel I have achieved a milestone in big data.

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2226 — 2250 de 2,439 Avaliações para o Introdução a Big Data

por Shilpashree M S

18 de jan de 2023



22 de ago de 2018


por Sheraz I

4 de jul de 2020


por Albouchi A

5 de ago de 2021


por Rishabh T

3 de jul de 2020



18 de mai de 2020


por Garvit T

15 de set de 2021



12 de out de 2020



5 de ago de 2020


por Arihant S J

18 de jun de 2020


por Sumit K

18 de jun de 2020


por Tejal C

9 de jun de 2020


por Chirag P

15 de mai de 2020



13 de mai de 2020


por Hyungje W

31 de out de 2018


por Mahmoud T

6 de jul de 2017


por Sweta c

27 de ago de 2020


por Kirk S

5 de mai de 2018

Quizzes appear to have been written by someone who simply went through the videos and slides and looked for things for the student could parrot back rather than by someone who was asking questions based on understanding of the material.

Videos is not a great medium for this kind of thing. It is slow and hard to review. I understand the desire to replicate a classroom experience, but without the ability to interrupt and ask a question, that isn't what you are creating. The transcript system is quite helpful in this regard, but really, if you just gave me a short text to read that clearly stated the things discussed in the video it would be more efficient.

por Michael L

28 de fev de 2020

The course is gives a good overview on big data as a topic. I personnally found the questions in the reviews sometimes arbitrary. I would have liked more implementation and a bit more technical flavour. At the same time the technical infrastructure (Cloudera virtual Machine) needs to be updated. It is bit messy working on a machine with such a bad screen resolution. E.g.: Unfortunately, installing the guest additions affects the functionality of haddop on the virtual machine. Thus, in the practical part one bothers more with technical issues than the actual implementation.

por Zsolt B

5 de set de 2016

The content of the course is alright and up to date. The instructors are also good, passionate and has a great knowledge.

What brings everything down is the video editing and the slide design/quality. They are terrible and clearly not in the field of profession of the creators.

All in all, it is an average course, but I can recommend it to anyone interesting in the topic, because it does its job. If someone could improve the slides and the video editing could reach the youtube video reviewer/critic level, it could easily do a 4 out of 5.

por Jonathan R

31 de out de 2022

It's a bit slow to start, especially if your reason for being here is already solid. It's always good to start from the "why", but we sat there for a very long time when I imagine most people come in knowing why they're doing this (though I could of course be wrong). The best part was the bit of hands on with Hadoop at the end, which I wish I had gotten more of. Also, the course probably needs an update as it uses a long deprecated version of VirtualBox, so much so that my computer would not let me use it for security reasons.

por Juan P

16 de jul de 2016

This is an introduction course, and no advanced concepts are seen. I think it provides a good background, that is all. If you have a solid technical (programming, databases, etc.) knowledge maybe you will miss more hand-ons. For me, for an introductory and theoretical course I expected more resources, for example additional suggested readings, optional exercises...

Lectures are well structured (intro and summary at the end), but I have missed presentations from some of the most interesting videos (week 6).

por Tomáš V

2 de set de 2022

The course probably provides a nice introduction to the topic of big data, but it seems that it focuses on useless terminology (that feels to be made up so that concepts like five P of big data and six V of big data can be used instead of normal language) a little bit too much. The course also seems to need some renewal - it seems that the original was made around year 2016 - the used programmes are not supported any more and I ran into some problems with the new versions.

por Kjell L

25 de ago de 2016

The course is ok but I found that there were some technical quirks that could be ironed out first. Example is to download the text files in the final assignment the command wget is invaluable. How to leave safe mode if the Name node is in safe mode. VirtualBox is default to 32 bit/ubuntu when the image is 64 bit/Centos/Redhat.

In addition the course content is a bit little. It says 3 weeks but I finish it in 2 days. Perhaps it is about quality and not quantity.

por CHU T K

1 de jun de 2019

Really difficult to understand for the new hand who don't knowledge the knowledge about programming, computer science, etc.

One of the difficulty is the many technique words. I suggest that providing the animation video to present some concept such as MapReduce should be more understandable.

However, after this lesson I can have a foundation perception in Big Data. Thanks for the Coursera, the University and course lecturers.