Official course description, subject to change:
Basic info last published 7/04-21

Advanced Data Systems

Course info
Language:
English
ECTS points:
15.0
Course code:
KSADDAS1KU
Participants max:
15
Offered to guest students:
yes
Offered to exchange students:
yes
Offered as a single subject:
yes
Price (single subject):
21250 DKK (incl. vat)
Programme
Level:
MSc. Master
Programme:
MSc in Computer Science
Staff
Course manager
Associate Professor
Teacher
Associate Professor
Course semester
Semester
Efterår 2021
Start
30 August 2021
End
31 December 2021
Exam
Abstract

In this course, you will both learn state-of-the-art techniques that power state-of-the-art data-intensive applications and systems running on modern hardware and get to apply these techniques on a modern data-intensive system.

Description

To transform the sheer amount of complex data into timely discoveries that influence the society, data-intensive systems (including database systems and machine learning platforms) must utilize the full processing power offered by modern processor and storage technologies.

In this course, you will learn the state-of-the-art techniques for data management and processing on modern hardware (multicores, hardware accelerators, microsecond-scale storage, and 100 GBE).

In parallel, you will apply some of these techniques on widely-used open-source data-intensive systems.

As a result, you will get hands-on experience with how to design, implement, and evaluate new components of an open-source data-intensive system.


Formal prerequisites

Computer Systems Performance class.

Intended learning outcomes

After the course, the student should be able to:

  • Analyze the functional and performance requirements of a data-intensive system (e.g., database system or machine learning platform)
  • Navigate the codebase of complex production-grade open-source software
  • Design and implement components in the context of a production-grade data system
  • * Evaluate the performance characteristics of a software system
  • Reflect upon the evolution of the hardware (processors, storage, networks) and its impact on the landscape of data-intensive systems and applications
  • Reflect upon research papers published by others and present research work to a broad technical audience
Ordinary exam
Exam type:
D: Submission of written work with following oral, Internal (7-point scale)
Exam variation:
D22: Submission with following oral exam supplemented by the submission.