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Bewertung und Feedback des Lernenden für Introduction to Big Data von University of California San Diego

10,506 Bewertungen

Über den Kurs

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+....



11. Aug. 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. Sep. 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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1926 - 1950 von 2,406 Bewertungen für Introduction to Big Data

von uday s

15. Okt. 2016

Very nice introduction to the core concepts of big data. Gradually introduced you to the concepts

von Michael J

27. Nov. 2020

I think that is better adding options of Cloudera, I used hortonworks and azure virtual machine


6. Juli 2020

Just an awesome course. My suggestion is that the ppt could be improved as it is sooooo simple.

von Aravind M

3. Aug. 2018

A good course for understanding the fundamentals of Big Data, HDFS and concepts like MapReduce.

von Daniel A M

5. Sep. 2021

Great amount of information and real life examples. Clear and precise explanations. Good job!

von ashutosh k

16. Dez. 2017

So far it is good to go... still i m perusing 2 more weeks of this course. So left one star.

von Mohamed E T

7. Juni 2017

More hand on exercises similar to the one at the end of the course would be very valuable.

von Visas V T

24. Feb. 2018

Great course. Explanation is good. Also gives good practical applications of each section

von Adnan B

27. Jan. 2017

Course is good to get initial background of Big Data and to understand What/Why Big Data.

von Kaddoum R

24. Sep. 2016

Content is very interesting, nice introduction to Big Data.

Slides can be improved though.

von Robert C

24. Juli 2017

useful, but the english is a bit sketchy at times and the explanations could be clearer

von Ian M

28. Dez. 2016

Excellent introduction to Big Data and Hadoop. Practical exercise reinforces materials.

von Javier E

8. Mai 2021

cool course, sad thing is that doesn't have instructions to work with hadoop on linux.

von Jorge d l V G

28. Aug. 2016

The material OK, but some of the exercises and their interfaces are not well designed.

von Prashanth K

26. Okt. 2018

Good introductory course, although more advanced concepts could have been intrdoduced

von David L M

12. Juni 2020

It is useful for beginners. However, I think the provided material could be updated.

von Cristhian M P V

7. Juni 2020

Good explanation, I would like you to continue improving with the audiovisual media.

von Cristian A

10. Mai 2020

The MapReduce exercise is a little confusing, specially after the vegetable example.

von Piyush P

5. Nov. 2018

Nice course but if programming part for map reduce was there it would be much better

von mike d

26. Apr. 2018

Dr. Altıntaş' presentation is rather choppy at first, but gets better after week 1.

von Victor O d S

17. Juni 2020

It's a great introduction to the big data. That's improve my vision about the area

von Madhu M

31. Mai 2020

A good introduction given for all basics of big data. clearly explained all topics


15. Mai 2020

The explanation and elaboration of the coding part is very good and very helpfull.

von Gopesh T

21. Jan. 2017

I learnt basic of Big Data, exicited to dive deeper.Very informative and engaging

von Md. M Z

9. Dez. 2017

I really enjoyed the course and learned a lot but contents could be much better.