Big Data - Capstone Project

Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions.*********Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. By following alo

Created by: Ilkay Altintas

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Overall Score : 88 / 100

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Course Description

Welcome to the Capstone Project for Big Data! In this culminating project, you will build a big data ecosystem using tools and methods form the earlier courses in this specialization. You will analyze a data set simulating big data generated from a large number of users who are playing our imaginary game "Catch the Pink Flamingo". During the five week Capstone Project, you will walk through the typical big data science steps for acquiring, exploring, preparing, analyzing, and reporting. In the first two weeks, we will introduce you to the data set and guide you through some exploratory analysis using tools such as Splunk and Open Office. Then we will move into more challenging big data problems requiring the more advanced tools you have learned including KNIME, Spark's MLLib and Gephi. Finally, during the fifth and final week, we will show you how to bring it all together to create engaging and compelling reports and slide presentations. As a result of our collaboration with Splunk, a software company focus on analyzing machine-generated big data, learners with the top projects will be eligible to present to Splunk and meet Splunk recruiters and engineering leadership.

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Instructor Details

Ilkay Altintas

Ilkay Altintas is the Chief Data Science Officer at the San Diego Supercomputer Center (SDSC), UC San Diego, where she is also the Founder and Director for the Workflows for Data Science Center of Excellence. Since joining SDSC in 2001, she has in the areas of computational data science and e-Sciences at the intersection of scientific workflows, provenance, distributed computing, bioinformatics, observatory systems, conceptual data querying, and software modeling. She is a co-initiator of and an active contributor to the popular open-source Kepler Scientific Workflow System. Ilkay Altintas received her Ph.D. degree from the University of Amsterdam in the Netherlands.

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4.4

128 total reviews

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By Sahil a on 17-Jun-18

Really disappointed with the Virtual Machine related exercises throughout the whole course, not only the capstone, where literally I have spent more time trying to figure out how to make it work and do not get any error message than actually learning big data. Very very frustrating.For sure not going to recommend this course to any friend.

By Gabriel L on 8-Feb-17

This course deserves no starts. There were no instructors answering the many questions raised by the students. There were no explanations for wrong answers, and so no opportunity to learn. I was helping other students understand the assignments, and spent extra time grading submissions as no teaching assistants were available to help.There were a couple of very good teachers in the specialization, however the structure is critically flawed and your time would be better spent studying on your own.Avoid not just the capstone, but this entire series.

By Kishan S on 22-Dec-18

nice final course to close out the whole specialization program.

By Nikhil on 10-Dec-18

Course is well designed and structured.

By David K on 22-Nov-18

Thank you Coursera and instructors for creating this course. The structure is very good. Looking forward for completing other specializations too. Thank you!!

By on 24-Nov-18

waoh.. it's incredible.. .. I strongly recommend this Capstone Project. Be sure to put on frank effort.THAKYOUSOMUCH

By Shriram J on 26-Nov-18

Very nice project! Uses a lot of the knowledge acquired in a funny way!!

By DANIEL F D S on 26-Nov-18

All the sessions were very informative and provided the required knowledge from basics.

By Nirupama S on 14-Nov-18

This is very helpful project where i have applied all learning through ouot journey of this course.Though it was time consuming but worth to invest time, which benefits to upskill my knowledge

By Alberto M C on 14-Nov-18

My name is Jose Antonio from Brazil. I am looking for a new Data Scientist career (https://www.linkedin.com/in/joseantonio11).I did this course to complete my CV in Big Data and better understand the technology. The course was excellent and the classes well taught by teachers.Thank you for the support, course quality and great classes.Regards.Jose Antonio.

By Mallikarjun C on 28-Feb-19

it's really useful to practice what you've learned in the previous course.

By Kunnan L on 27-Dec-18

This is great platform to enhance your skills with periodic learning even from busy schedule and make yourself in pace with new IT.