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Cloud Computing and Big Data (Fall 2015)

Course Description:

Cloud Computing and Big Data are two trending technologies exciting most of the individuals and businesses. Cloud Computing provides huge computation and storage resources on demand. Large user-base is attracted to use Cloud Computing mainly due to pay-per-usage and on-demand resource provisioning characteristics. Nowadays, Big Data is continuously generated through sensors, mobile devices, social media, server logs, medical records etc. Combining Big Data and Cloud Computing technologies help us to develop innovative services and solutions. This course will introduce topics related to Cloud Computing and Big Data in detail. In this course, students will also get hands-on experience of using Amazon Web Services. 


    Lectures Plan
    •  Week 01:  Introduction to Cloud Computing
    • Week 02: Introduction to Big Data
    • Week 03: Virtualization
    • Week 04: Low Cost Quality Aware Application Hosting on the Amazon Cloud  
    • Week 05-06: Fundamentals of Distributed System
    • Week 07: NoSQL
    • Week 08 Midterm
    • Week 09: MapReduce
    • Week 10: Web Application Deployment Models
    • Week 11: Introduction to Data Mining
    • Week 12: Student Presentations
    • Week 13: Student Presentations 
    • Week 14: Scalable Web Application on the  Cloud
    • Week 15: IoT and Research Projects



    Assignments
     Assignment  Submission Template  Deadline
    Assignment 01: Launch, Connect, and Use an EC2 Instance
    		 Report Template
    Assignment 02: Images to PDF Conversion service over AWS Report Template

    Assignment 03: Performance measurement of web application on AWS Report Template
    Helping Material

    Assignment 04: Auto-scaling web application hosted on AWS Report Template



    Related Text / Reading Material:

    Jothy Rosenberg  and Arthur Mateos; The Cloud at Your Service; Manning Publications. ISBN: 1935182528

    ·         Paul Zikopoulos and Chris Eaton; Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data; McGraw-Hill. ISBN: 0071790535

    ·         Anand Rajaraman and Jeffrey David Ullman; Mining of Massive Datasets; Cambridge University Press. ISBN: 1107015359

    Grading Scheme/Criteria:

    Research Paper Presentation: 5%

    Project/Assignments:  15%

    Quizzes: 5%

    Midterm Exam:  25%

    Final:  50%