Official course description:

Basic info last published 7/11-18
Course info
Language:
English
ECTS points:
7.5
Course code:
BSLASDA1KU
Offered to guest students:
-
Offered to exchange students:
Offered as a single subject:
-
Programme
Level:
Bachelor
Programme:
BSc in Data Science
Staff
Course semester
Semester
Forår 2019
Start
28 January 2019
End
31 May 2019
Exam
Abstract

Turning the unprecedented amounts of data being collected today into useful information is well beyond the computing power of a single general purpose CPU core. It is, therefore, crucial to know and understand the methods and tools that are able to parallelize various data analysis tasks in an efficient way on multicore CPUs and on a cluster of machines.

With this goal in mind, this course first gives an overview of the popular parallel data processing platforms. Then, it dives into parallelizing various machine learning tasks.


Description

NA

Formal prerequisites
The course assumes that the students have taken an introductory course on data management or database systems.
Intended learning outcomes

After the course, the student should be able to:

  • Select the right distributed data processing platform and the right subset of functionalities from such platforms for a given task.
  • Apply machine learning and data mining in a parallel setting
  • Effectively combine different types of data analysis tasks (machine learning, traditional SQL, …) in a query
  • Reason about the performance of data processing systems in a parallel setting