Introduction to Big Data Analytics

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3/10 stars
based on  5 reviews
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Course Details

Cost

FREE

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  • In Session

Course Provider

Coursera online courses
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with yo...
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with your coursework. Coursera also partners with the US State Department to create “learning hubs” around the world. Students can get internet access, take courses, and participate in weekly in-person study groups to make learning even more collaborative. Begin your journey into the mysteries of the human brain by taking courses in neuroscience. Learn how to navigate the data infrastructures that multinational corporations use when you discover the world of data analysis. Follow one of Coursera’s “Skill Tracks”. Or try any one of its more than 560 available courses to help you achieve your academic and professional goals.

Provider Subject Specialization
Humanities
Sciences & Technology
4733 reviews

Course Description

********* A new, improved version of the Big Data Specialization will become available on June 6! As such, enrollment for this course and all courses in this original Big Data Specialization will close on June 6. The original Big Data Specialization will continue to run until September 2016, when the Capstone will be offered for learners in this version of the Specialization. If you are in the middle of the Specialization and have purchased the entire original Big Data Specialization before June 6, Coursera will reach out to you to offer you the option of staying in the original Specialization or taking the new version. If you are just getting started on this Specialization, we recommend that you wait until June 6 to enroll in the new version. ********* This course is for novice programmers or business people who'd like to understand more advanced tools used to wrangle and analyze big data. In this course you will be guided ... ********* A new, improved version of the Big Data Specialization will become available on June 6! As such, enrollment for this course and all courses in this original Big Data Specialization will close on June 6. The original Big Data Specialization will continue to run until September 2016, when the Capstone will be offered for learners in this version of the Specialization. If you are in the middle of the Specialization and have purchased the entire original Big Data Specialization before June 6, Coursera will reach out to you to offer you the option of staying in the original Specialization or taking the new version. If you are just getting started on this Specialization, we recommend that you wait until June 6 to enroll in the new version. ********* This course is for novice programmers or business people who'd like to understand more advanced tools used to wrangle and analyze big data. In this course you will be guided in basic approaches to querying and exploring data using higher level tools built on top of a Hadoop Platform. You will be walked through query interfaces, environments, and the canonical situations for tools like HBASE, HIVE, Pig, as well as more general tools like Spark-SQL. After this course you will be able to identify the kinds of analysis you can get of big data and how to interpret these results.
Introduction to Big Data Analytics course image
Reviews 3/10 stars
5 Reviews for Introduction to Big Data Analytics

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Rankings are based on a provider's overall CourseTalk score, which takes into account both average rating and number of ratings. Stars round to the nearest half.

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jac profile image
jac profile image
2/10 starsDropped
  • 5 reviews
  • 4 completed
4 years ago
I dropped this course when the first assignment was pretty much "use the VM you set up in our previous course to do x", with no further details (and no hint on enrolment that the previous course was a necessary prerequisite).
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2/10 starsTaking Now
3 years, 7 months ago
The course content is absolutely unprofessional. Videos contain obvious mistakes, and virtual machine that is used for practical training misses the files required to pass assignments.
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Angel T profile image
Angel T profile image
2/10 starsDropped
  • 3 reviews
  • 1 completed
3 years, 7 months ago
This course offers no more than reading the Hadoop tutorials by yourself. I don't need to pay for doing that. The examples are extremely basic and the tests want the student to memorize but no reasoning over the concepts explained.
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2/10 starsDropped
4 years ago
Very badly described, being able to complete is dependent on having done previous course. This is not even referred to in materials much less explained . Forum discussions and questions not answered. Waste of time and not what is expected from Coursera. Shame for an interesting topic.
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2/10 starsTaking Now
  • 1 review
  • 0 completed
4 years ago
Absolutely terrible. I've taken other Coursera classes and this is the worst I've encountered. Almost complete absence of course instructors or assistants in the discussion forums. Poor preparation of course materials. Incomprehensible quiz questions and answers. Nearly impossible to complete in some cases. As an example, one quiz requires you to derive answers from a dataset in Splunk, but the dataset they expect you to use is UPDATED DAILY (the instructor even states this fact in the lecture). The answers when the quiz was written are no longer the answers you get with the current data, and they don't provide a copy of the dataset used to create the quiz. You must simply guess the quiz answers and repeat the quiz until you guess enough correctly to pass.
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