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Algorithms for Big Data Processing 7.5 credits

Algoritmer för stora datamängder
Second cycle, D7036E
Course syllabus valid: Spring 2022 Sp 3 - Present
The version indicates the term and period for which this course syllabus is valid. The most recent version of the course syllabus is shown first.

Education level
Second cycle
Grade scale
G U 3 4 5
Computer Science
Subject group (SCB)
Computer Technology

Entry requirements

The student should have knowledge about basic algorithms and data structures, discrete mathematics, and probability. For example: D0012E - Algorithms and Data Structures, M0009M - Discrete Mathematics and S0001M - Mathematical Statistics.

More information about English language requirements


The selection is based on 20-285 credits

Course Aim

After completing the course the student should be able to:

  • demonstrate knowledge of the disciplinary foundation and of proven experience in the design and analysis of algorithms and data structures for large data sets
  • demonstrate the ability to construct, analyze and critically evaluate various algorithmic solutions for large data sets with respect to correctness, efficiency, and reliability
  • show knowledge of mathematical tools for designing and analyzing algorithms for large data sets
  • demonstrate insight in the scientific state of the art in algorithms for large data sets
  • demonstrate the ability to model, predict and evaluate the events even with limited information

Topics covered include: paradigms and models, data stream algorithms, parallel algorithms, cache-oblivious algorithms.

Each course occasion´s language and form is stated and appear on the course page on Luleå University of Technology's website.
Lectures, laborations/projects, and seminars.

If there is a decision on special educational support, in accordance with the Guideline Student's rights and obligations at Luleå University of Technology, an adapted or alternative form of examination can be provided.
Seminars, assignments, compulsory attendance, oral and written presentation of projects. The final grade will be based on performance in all modules.

Jingsen Chen

Literature. Valid from Spring 2016 Sp 3 (May change until 10 weeks before course start)
Scientific publications (conference papers and journal articles).

Course offered by
Department of Computer Science, Electrical and Space Engineering

CodeDescriptionGrade scaleCrStatusFrom periodTitle
0003Project and assignmentsG U 3 4 55.00MandatoryS22
0004Seminars and attendenceU G#2.50MandatoryS22

Study guidance
Study guidance for the course is to be found in our learning platform Canvas before the course starts. Students applying for single subject courses get more information in the Welcome letter. You will find the learning platform via My LTU.

Syllabus established
by Jonny Johansson, HUL SRT 16 Feb 2015

Last revised
by Jonny Johansson, HUL SRT 17 Feb 2021