Course Summary
This course teaches learners how to apply big data technologies to real-world problems and projects. Students will be able to identify the benefits of using big data in various fields and learn the tools and techniques needed to use it for their own projects.Key Learning Points
- Understand the basics of big data and its applications in various fields
- Learn how to use Hadoop and Spark for big data processing
- Apply big data tools and techniques to real-world projects
Related Topics for further study
Learning Outcomes
- Understand the fundamentals of big data technologies and its applications in various fields
- Use Hadoop and Spark for processing large datasets
- Apply big data tools and techniques to real-world problems and projects
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of programming
- Familiarity with data structures and algorithms
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Big Data Analytics
- Big Data Essentials: HDFS, MapReduce and Spark RDD
Notable People in This Field
- Chief Architect at Cloudera
Related Books
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.
Outline
- Simulating Big Data for an Online Game
- Welcome to the Big Data Capstone Project
- Welcome from Splunk: Rob Reed World Education Evangelist
- A Summary of Catch the Pink Flamingo
- A Conceptual Schema for Catch the Pink Flamingo
- Planning, Preparation, and Review
- A Game by Eglence Inc. : Catch The Pink Flamingo
- Overview of the Catch the Pink Flamingo Data Model
- Overview of Final Project Design
- Acquiring, Exploring, and Preparing the Data
- Downloading the Game Data and Associated Scripts
- Understanding the CSV Files Generated by the Scripts
- “Catch the Pink Flamingo” Data Exploration with Splunk
- Aggregate Calculations Using Splunk
- Filtering the Data With Splunk
- Data Exploration With Splunk
- Data Classification with KNIME
- Review: Classification Using Decision Tree in KNIME
- Review: Interpreting a Decision Tree in KNIME
- Workflow Overview for Building a Decision Tree in KNIME
- Description of combined_data.csv
- Clustering with Spark
- Informing business strategies based on client base
- Practice with PySpark MLlib Clustering
- Graph Analytics of Simulated Chat Data With Neo4j
- Understanding the Simulated Chat Data Generated by the Scripts
- Graph Analytics of Catch the Pink Flamingo Chat Data Using Neo4j
- Reporting and Presenting Your Work
- Week 5: Bringing It All Together
- Final project preparation
- Final Submission
- Congratulations! Some Final Words...
- Part 2: Help us connect your video to your LinkedIn profile
Summary of User Reviews
The Big Data Project course on Coursera is highly rated by users who enjoyed the practical approach and real-world examples. Many users appreciated the hands-on experience the course provides, allowing them to apply the concepts learned immediately.Pros from User Reviews
- Hands-on experience and practical approach
- Real-world examples and case studies
- In-depth coverage of Big Data concepts
- Great for beginners and intermediate learners
- Engaging and knowledgeable instructors
Cons from User Reviews
- Not suitable for advanced learners
- Lack of depth in certain topics
- Limited interaction with instructors
- Some technical issues with the platform
- Lack of flexibility in course schedule
Ilkay Altintas
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