Course: Big Data Analysis

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This schedule is tentative and subject to change

Make sure to check my.poly.edu for course announcements

Week 1: Monday Sept. 10th - Course Overview


Required Readings

Additional References

Week 2: Monday Sept. 17th - Map-Reduce

  • Introduction to Map-Reduce
  • Introduction to [1]
  • The Map-Reduce ecosystem: Pig, Hive, Jaql, Mahout, BigInsights

Required Readings

Additional References

Week 3: Monday Sept. 24th - Databases and Big Data

Readings

Week 4: Monday Oct. 1st - Statistics is easy - Invited Speaker: Dennis Shasha

Readings


Week 5: Monday Oct. 8st - Finding Similar Items

  • Overview of information integration

Readings

Week 6: Monday Oct. 15st - Invited Speaker: Torsten Suel

  • Reading: inverted index and crawling (Lin chapter 4)
  • Ask Torsten (tentative, ask him for reading material)

Readings

Week 7: Monday Oct. 22st - Invited Speakers: Claudio Silva and Lauro Lins

  • Introduction to Visualization; Data stewardship and provenance
  • Guest lecture by Claudio Silva and Lauro Lins

Readings

  • Hellerstein (ask Claudio for additional references)
  • ADD: provenance and reproducibility

Week 8: Monday Oct. 29th - Graph Analysis

  • Graph algorithms, link analysis, social networks

Readings

  • Data-Intensive Text Processing with MapReduce, Chapter 4


Week 9: Monday Nov. 5th - Frequent Itemsets

Reading

  • Mining of Massive Datasets, Chapter 6


Week 10: Monday Nov. 12th - Mining Data Streams =

Readings

  • Mining of Massive Datasets, Chapter 4


Week 11: Monday Nov. 19th - Clustering

Readings

  • Mining of Massive Datasets, Chapter 7

Week 12: Monday Nov. 26th - Recommendation Systems

Readings

  • Mining of Massive Datasets, Chapter 9

Week 13 Monday Dec. 3rd - EM algorithms for text processing

  • Data-Intensive Text Processing with MapReduce, Chapter 6

Week 14: Monday Dec. 10th - Project presentation

Further Readings