Difference between revisions of "Course: Big Data 2014"

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* Required reading:  
* Required reading:  
** Data-Intensive Text Processing with MapReduce, Chapters 1 and 2
** Data-Intensive Text Processing with MapReduce, Chapters 1 and 2
** Mining of Massive Datasets (2nd Edition), Chapter 2 - 2.1 and 2.2 (Large-Scale File Systems and Map-Reduce.
** Mining of Massive Datasets (2nd Edition), Chapter 2 - 2.1 and 2.2 (Large-Scale File Systems and Map-Reduce).


* Other useful reading:  
* Other useful reading:  
Line 82: Line 82:
* Homework Assignment -- Your first quiz is available on [http://www.newgradiance.com Gradiance]. It is ''due on March 17th at 5pm.''
* Homework Assignment -- Your first quiz is available on [http://www.newgradiance.com Gradiance]. It is ''due on March 17th at 5pm.''


== Week 6 -- Mar 10: Data Management for Big Data ==
== Week 6 -- Mar 10: Algorithm Design for MapReduce  ==


== Week 7 -- Mar 24: No-SQL and NewSQL Systems ==
* Lecture notes: 
** http://vgc.poly.edu/~juliana/courses/BigData2014/Lectures/mapreduce-algo-design.pdf
 
* Required reading:
** Data-Intensive Text Processing with MapReduce, Chapters 1 and 2
** Mining of Massive Datasets (2nd Edition), Chapter 2.
 
 
== Week 7 -- Mar 24: Data Management for Big Data, No-SQL and NewSQL Systems ==


== Week 8 -- Mar 31: Query Processing on Mapreduce and High-level Languages ==
== Week 8 -- Mar 31: Query Processing on Mapreduce and High-level Languages ==


= Big Data Algorithms and Techniques (6 weeks) =
= Big Data Algorithms and Techniques (6 weeks) =

Revision as of 22:06, 10 March 2014

DS-GA 1004/CSCI-GA 2568 Big Data: Tentative Schedule -- subject to change

  • Lecture: Mondays, 7:10pm-9:00pm at Cantor, room 101. Note new location!
    • Cantor Film Center (CANTR), 36 E 8th St, New York, NY 10003
  • Lab: Thursdays, 7:10pm-8:00pm at CIWW, room 109. Always bring your laptop.
    • Warren Weaver Hall (CIWW), 251 Mercer St, New York, NY 10012

News

  • Starting on Feb 10th, our class will meet at a new location: Cantor 101
  • We will have lab on Thu at CIWW, room 109. Bring your laptop!

Background (4 weeks)

Week 1 -- Jan 27: Course Overview; the evolution of Data Management


Week 2 -- Feb 3: Introduction to Databases

Week 3 -- Feb 10: Overview: Relational Model and SQL

  • Feb 13: Lab: Canceled -- University closed due to snow ==


Week 3.1 -- Feb 17


Week 4 -- Feb 24: Overview: Advanced SQL and Query Optimization

Big Data Foundations and Infrastructure (4 weeks)

Week 5 -- Mar 3: Cloud computing, Map Reduce and Hadoop

  • Required reading:
    • Data-Intensive Text Processing with MapReduce, Chapters 1 and 2
    • Mining of Massive Datasets (2nd Edition), Chapter 2 - 2.1 and 2.2 (Large-Scale File Systems and Map-Reduce).
  • Homework Assignment -- Your first quiz is available on Gradiance. It is due on March 17th at 5pm.

Week 6 -- Mar 10: Algorithm Design for MapReduce

  • Required reading:
    • Data-Intensive Text Processing with MapReduce, Chapters 1 and 2
    • Mining of Massive Datasets (2nd Edition), Chapter 2.


Week 7 -- Mar 24: Data Management for Big Data, No-SQL and NewSQL Systems

Week 8 -- Mar 31: Query Processing on Mapreduce and High-level Languages

Big Data Algorithms and Techniques (6 weeks)

Week 9 -- Apr 7: Map Reduce Algorithm Design

Week 10 -- Apr 14: Finding similar items and information integration

Week 11 -- Apr 21: Graph Analysis

Week 12 -- Apr 28: Frequent Itemset Mining

Week 13 -- May 5: Interactive Analysis and Visualization of Big Data

Week 14 -- May 12: Machine Learning for Big Data

Week 15 -- May 19: Final Exam