Course: Big Data 2016

From VistrailsWiki
Jump to navigation Jump to search
The printable version is no longer supported and may have rendering errors. Please update your browser bookmarks and please use the default browser print function instead.

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

  • TAs:
    • Yuan Feng
    • Kevin Ye
  • Lecture: Mondays, 4:55pm-7:35pm at Silver 207
  • 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 and Relational Model

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

Week 4 - Feb 15: Holiday

Transparency and Reproducibility (1 week)

Week 5 - Feb 22: Data Exploration and Reproducibility

Big Data Foundations and Infrastructure (3 weeks)

Week 6 - Feb 29: Introduction to Map Reduce

Week 7 - March 7: MapReduce Algorithm Design Patterns

Week 8-- March 14th: Spring Break

Week 9- March 21st: Parallel Databases vs MapReduce; Storage Solutions; Introduction to SPARK

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

Week 10 - March 28th: Finding similar items & Spark

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

Week 11 - April 4th: Large-Scale Visualization -- -- Invited lecture by Professor Claudio Silva


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

Week 13 - April 18th: Data Cleaning - Invited lecture by Dr. Divesh Srivastava, AT&T Research

Week 14 - April 25th: 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

Week 15 - May 2: Graph Analysis

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


Week 16 - May 9: Final Exam

Week 17 - May 16: Project Presentations