Big Data: Architectures and Data Analytics (2020/2021)


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Table of content

General information

  • ECTS: 6
  • Professor: Paolo Garza
  • Teaching assistants:
    • Luca Colomba
    • Francesco Ventura

Exam rules

  • Exam rules Academic Year 2020-2021 (link)

Announcements

  •  (24/09/2020)
    • First (online) lecture: Tuesday, September 29 at 13.00 – Online virtual classroom
  • (24/09/2020)
    • No lab activities during the first two weeks.
    • The lab activities scheduled for Monday, September 28 from 17:30 to 19:00 and Tuesday, September 29 from 8:30 to 10:00 are cancelled.

Slides

Exercises

Practices

  • No lab activities during the first two weeks
  • TEAM 1: Students from A to H – Monday from 5.30 pm to 7 pm
  • TEAM 2: Students from I to Z – Tuesday from 8.30 am to 10 am

Exam Examples

Pay attention that from this academic year (2020/21) the exam is closed book

  • Exam June 26, 2018
    • Exam – Version #1 (pdf)
      • Draft of the solution
        • Question 1: (c)
        • Question 2: (c)
        • Source code/Eclipse projects (zip)
    • Exam – Version #2 (pdf)
      • Draft of the solution
        • Question 1: (b)
        • Question 2: (c)
        • Source code/Eclipse projects (zip)
  • Exam July 16, 2018
    • Exam – Version #1 (pdf)
      • Draft of the solution
        • Question 1: (d)
        • Question 2: (a)
        • Source code/Eclipse projects (zip)
    • Exam – Version #2 (pdf)
      • Draft of the solution
        • Question 1: (b)
        • Question 2: (d)
        • Source code/Eclipse projects (zip)
  • Exam September 3, 2018
    • Exam – Version #1 (pdf)
      • Draft of the solution
        • Question 1: (d)
        • Question 2: (c)
        • Source code/Eclipse projects (zip)
    • Exam – Version #2 (pdf)
      • Draft of the solution
        • Question 1: (b)
        • Question 2: (c)
        • Source code/Eclipse projects (zip)
  • Exam February 15, 2019
    • Exam – Version #1 (pdf)
      • Draft of the solution
        • Question 1: (d)
        • Question 2: (c)
        • Source code/Eclipse projects (zip)
    • Exam – Version #2 (pdf)
      • Draft of the solution
        • Question 1: (d)
        • Question 2: (b)
  • Exam July 2, 2019
    • Exam – Version #1 (pdf)
      • Draft of the solution
        • Question 1: (a)
        • Question 2: (b)
        • Source code/Eclipse projects (zip)
    • Exam – Version #2 (pdf)
      • Draft of the solution
        • Question 1: (a)
        • Question 2: (b)
        • Source code/Eclipse projects (zip)
  • Exam July 18, 2019
    • Exam – Version #1 (pdf)
      • Draft of the solution
        • Question 1: (b)
        • Question 2: (b)
        • Source code/Eclipse projects (zip)
    • Exam – Version #2 (pdf)
      • Draft of the solution
        • Question 1: (c)
        • Question 2: (b)
        • Source code/Eclipse projects (zip)
  • Exam July 2, 2020
    • Exam (pdf)
      • Draft of the solution
        • Question 1: (b)
        • Question 2: (a)
        • Source code/Eclipse projects (zip)
  • Exam July 16, 2020
    • Exam (pdf)
      • Draft of the solution
        • Question 1: (b)
        • Question 2: (b) – Note that there are two actions and hence the input file is read two times.
        • Source code/Eclipse projects (zip)
  • Exam September 17, 2020
    • Exam (pdf)
      • Draft of the solution
        • Question 1: (d)
        • Question 2: (c)
        • Source code/Eclipse projects (zip)
  • Exam February 5, 2021
    • Exam (pdf)
      • Draft of the solution
        • Question 1: (b)
        • Question 2: (c)
        • Source code/Eclipse projects (zip)
  • Exam June 30, 2021
    • Exam (pdf)
      • Draft of the solution
        • Question 1: (a)
        • Question 2: (c)
        • Source code/Eclipse projects (zip)

Additional material

  • Slides and screencasts about Java (kindly provided by prof. Torchiano) (link)
    • Suggested slides/lectures for those students who have never used Java
      • OO Paradigm and UML (The UML part is not mandatory)
      • The Java Environment
      • Java Basic Features
      • Java Inheritance
  • Data mining – Centralized algorithms
    • Data and Preprocessing (slides)
    • Itemset mining and Association rules (slides)
    • Classification (slides) (slidese)
    • Clustering (slides) (slides)