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Dades generals

 

Nom de l'assignatura: Dades Massives

Codi de l'assignatura: 572667

Curs acadčmic: 2020-2021

Coordinació: Jordi Vitria Marca

Departament: Departament de Matemątiques i Informątica

crčdits: 3

Programa śnic: S

 

 

Programari

 

API spark, http://spark.apache.org/docs/latest/api.html 

 

 

Hores estimades de dedicació

Hores totals 75

 

Activitats presencials i/o no presencials

30

 

-  Teoricoprąctica

Presencial i no presencial

 

30

 

(Blended learning. )

Treball tutelat/dirigit

15

Aprenentatge autņnom

30

 

 

Competčncies que es desenvolupen

 

Learn the difference between classical computing and big data computing.

 

Learn to use a big data cloud infrastructure.

 

Learn how to store massive data sets.

 

Learn how to deal with high-velocity data sources.

 

Learn how to process massive data sets.

 

Learn how to manage the life-cycle of data science projects.

 

 

 

 

Objectius d'aprenentatge

 

Referits a coneixements

Most of date science problems involve to work with big volumes of information that has be stored, cleaned and processed to be useful for machine learning algorithms. This subject focuses on explaining how to develop and end-tone-end data science application to allow students to develop data products based on big data technologies.

 

 

Blocs temątics

 

1. Introduction to Big Data.

*  Introduction to classical computing

Evolution of Infrastructure

Evolution of Big Data

What is Big data (The five Vs)

Need for Big data infra

2. Introduction to Cloud Infrastructure

3. Introduction to Docker and Kubernetics

4. Big Data Storage

5. Big Data Ingestion

6. Big Data Processing

7. Data Science Life cycle Management

 

 

Metodologia i activitats formatives

 

Due to the health emergency of COVID-19 and during the 2020-2021 academic year, the subject will follow a model of blended teaching instead of face-to-face. The division of students into groups will be adapted to this situation. Teaching will be structured as follows:

  • Weekly, there is an asynchronous one-hour session where the students autonomously work in the subject.
  • Weekly, there is a face-to-face one-hour session corresponding to theoretical-practical activities.


If the health situation allows it, we will move to a face-to-face teaching style. In this case, the hourly load remains at the same values, but all classes are held in face-to-face mode, and the distribution of students in groups can be varied to suit the face-to-face mode.

 

 

 

Avaluació acreditativa dels aprenentatges

 

The requirements for this course consist of an exam and 2 assignments. The grading breakdown is the following:

  • Homework (60%, 2 assignments, 30% each)
  • Exam (40%)

 

Avaluació śnica

Exam (100%)