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.
This course is part of the Big Data Specialization
Offered By
Big Data SpecializationUniversity of California San DiegoAbout this Course
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- Big Data
- Neo4j
- Knime
- Splunk
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Syllabus - What you will learn from this course
Simulating Big Data for an Online Game
Acquiring, Exploring, and Preparing the Data
Data Classification with KNIME
Clustering with Spark
Graph Analytics of Simulated Chat Data With Neo4j
Reviews
- 5 stars66.06%
- 4 stars21.85%
- 3 stars5.91%
- 2 stars1.79%
- 1 star4.37%
TOP REVIEWS FROM BIG DATA - CAPSTONE PROJECT
I learned a lot about applying the big data knowledge gained in the previous courses. Thank you!
Excellent course, 100% recommend to people want to learn big data fundamentals.
This is great platform to enhance your skills with periodic learning even from busy schedule and make yourself in pace with new IT.
I only realized how good this specialization was when I took a course from another university.
About the Big Data Specialization
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