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Course: Big Data 2016

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* 1/25/2016: An HPC account has been created for you. You will need this account for in-class exercises and homework assignments. See  [[NYU HPC Access Instructions]]
* 1/25/2016: An HPC account has been created for you. You will need this account for in-class exercises and homework assignments. See  [[NYU HPC Access Instructions]]
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== Week 1 - Jan 25:  Course Overview; Lab: Computing infrastructure for the course ==
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== Week 1 - Jan 25:  Course Overview ==
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* Lecture notes:  http://vgc.poly.edu/~juliana/courses/BigData2016/Lectures/course-overview.pdf
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* '''Lecture notes:''' http://vgc.poly.edu/~juliana/courses/BigData2016/Lectures/course-overview.pdf
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* Reading: Chapter 1 of Mining of Massive Data Sets (version 1.1)
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*''' Lab:'''  Computing infrastructure for the course
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* Course survey: https://docs.google.com/forms/d/1LTiJwkDVvp0cF62Fw_d9Y86US5LCkorRUIQtV2T8KWE/viewform?usp=send_form
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* '''Reading:''' Chapter 1 of Mining of Massive Data Sets (version 1.1)
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* '''Course survey:''' https://docs.google.com/forms/d/1LTiJwkDVvp0cF62Fw_d9Y86US5LCkorRUIQtV2T8KWE/viewform?usp=send_form
== Week 2 - Feb 1:  The evolution of Data Management and introduction to Big Data; Introduction to Databases, Relational Model and SQL==
== Week 2 - Feb 1:  The evolution of Data Management and introduction to Big Data; Introduction to Databases, Relational Model and SQL==
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* In-class assignment: relational algebra
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* '''Lecture notes:'''
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** http://vgc.poly.edu/~juliana/courses/BigData2016/Lectures/datamanagement.pdf
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** http://vgc.poly.edu/~juliana/courses/BigData2016/Lectures/intro-db.pdf
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* '''Lab:''' in-class assignment on relational algebra
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* '''Readings:'''
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** [http://philip.greenspun.com/sql/introduction.html Greenspun's SQL for Web Nerds Intro]
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** [http://philip.greenspun.com/sql/data-modeling.html SQL/Nerds Modeling (parts)]
== Week 3 - Feb 8: Introduction to Databases, Relational Model and SQL (cont.) ==
== Week 3 - Feb 8: Introduction to Databases, Relational Model and SQL (cont.) ==
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* Lab: SQL
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*''' Lecture notes:''' http://vgc.poly.edu/~juliana/courses/BigData2016/Lectures/intro-db.pdf
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* Programming assignment: Using SQL for data analysis and cleaning  
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* '''Lab:''' SQL  
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* '''Programming assignment:''' Using SQL for data analysis and cleaning (check NYU Classes)
== Week 4 - Feb 15: Holiday ==
== Week 4 - Feb 15: Holiday ==
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== Week 5 - Feb 22:  Introduction to Map Reduce ==
== Week 5 - Feb 22:  Introduction to Map Reduce ==
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*''' Lecture notes:''' http://vgc.poly.edu/~juliana/courses/BigData2016/Lectures/mapreduce-intro.pdf
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* '''Lab:''' Hands-on Hadoop (local and AWS)
* Quiz 1 (Map Reduce) -- check http://www.newgradiance.com/services
* Quiz 1 (Map Reduce) -- check http://www.newgradiance.com/services
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* Lab: Hands-on Hadoop (local and AWS)
 
== Week 6 - Feb 29: MapReduce Algorithm Design Patterns  ==
== Week 6 - Feb 29: MapReduce Algorithm Design Patterns  ==
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* Lab: Hands-on Hadoop (HPC)
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*''' Lecture notes:''' http://vgc.poly.edu/~juliana/courses/BigData2015/Lectures/mapreduce-algo-design.pdf
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* Programming assignment: Map Reduce (check NYU Classes)
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* '''Lab:''' Hands-on Hadoop (HPC)
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* '''Programming assignment:''' Map Reduce (check NYU Classes)
== Week 7 - March 7: Parallel Databases vs MapReduce; Introduction to SPARK==  
== Week 7 - March 7: Parallel Databases vs MapReduce; Introduction to SPARK==  

Revision as of 15:55, 23 January 2016

Contents

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

  • TAs:
    • Yuan Feng
    • Kevin Ye
  • Lecture: Mondays, 4:55pm-7:35pm at 19 University Pl., room 102.
  • Some classes will include a lab session, please always bring your laptop.

News

Week 1 - Jan 25: Course Overview

Week 2 - Feb 1: The evolution of Data Management and introduction to Big Data; Introduction to Databases, Relational Model and SQL

Week 3 - Feb 8: Introduction to Databases, Relational Model and SQL (cont.)

Week 4 - Feb 15: Holiday

Big Data Foundations and Infrastructure (3 weeks)

Week 5 - Feb 22: Introduction to Map Reduce

Week 6 - Feb 29: MapReduce Algorithm Design Patterns

Week 7 - March 7: Parallel Databases vs MapReduce; Introduction to SPARK

  • Lab: Hands-on SPARK (HPC)
  • Programming assignment: check NYU Classes on March 10th

Week 8 -- March 14th: Spring Break

Transparency and Reproducibility (1 week)

Week 9 - March 21: Data Exploration and Reproducibility

  • Programming assignment 4: Exploring urban data (see NYU Classes)

Big Data Algorithms, Mining Techniques, and Visualization (6 weeks)

Week 10 - March 28th: Finding similar items

  • Homework Assignment
    • See quizzes on Gradiance -- Distance measures and document similarity.

Week 11 - April 4th: Association Rules


  • Suggested additional reading:
    • Fast algorithms for mining association rules, Agrawal and Srikant, VLDB 1994.
    • Data Mining Concepts and Techniques, Jiawei Han and Micheline Kamber, Morgan Kaufmann
    • Dynamic Itemset Counting and Implication Rules for Market Basket Data. Brin et al., SIGMOD 1997. http://www-db.stanford.edu/~sergey/dic.html
  • Homework Assignment
    • See quizes on Gradiance -- Distance measures and document similarity.

Week 12 - April 11th: Visualization and Spatio-Temporal Data -- Invited lecture by Dr. Harish Doraiswamy (NYU CUSP)

Week 13 - April 18th: Parallel Databases

Week 14 - April 25th: Graph Analysis

  • Required Reading: Data-Intensive Text Processing with MapReduce. Chapters 5 -- Graph Algorithms

Week 15 - May 2: Final Exam

Week 16 - May 9: Project Presentations

Week 17 - May 16: Project Presentations

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