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Big data processing and applications

Individual course

Max amounts of FITech students: 30

Persons without a valid study right to a Finnish university have preference to this course.

During this course, the student gets familiar with the concept of “Big data” and different phenomena related to it, including requirements and principles for data intensive systems and their implementation as well as benefits, risks and restrictions of available big data solutions.

Course topics include general introduction into big data, namely: big data fundamentals, data storage, batch and stream data processing, data analysis, privacy and security, big data use cases.

Upon completion of the course, the student

  1. can identify real life cases where big data solutions are needed and design basic solutions to big data problems.
  2. is able to explain the big data phenomenon, its challenges and opportunities
  3. is able to explain the requirements and common principles for data intensive systems design and implementation, and evaluate the benefits, risks and restrictions of available solutions
  4. can explain the principles of big data management and processing technologies and utilize them on a basic level.

The course includes face-to-face teaching, lectures, exercises, seminars as well as independent and group work. Also online possibilities within the course schedule. No exam.

You can get a digital badge after completing this course.

data-analytiikka data-analyysi massadata datan käsittely data science data processing

Further information about the courses and studying

University of Oulu
Riku Hietaniemi , ICT coordinator

Responsible teacher

University of Oulu
Lauri Loven

Contact person for applications

FITech Network University
Monica Sandberg
Start here
Start here
ICT Studies
AI and machine learning,
Data analytics
Course code:
0 €
Teaching period:
Application deadline:
Application period has ended
Host university:
University of Oulu
Study is open for:
Adult learner,
Degree student
Teaching methods:
Place of contact learning:
General prerequisites:
This course is suitable for students who have Bachelor degree in computer science (or similar) or background in data intensive systems. Suggested prequisite courses are "Towards data mining" and "Machine learning".
Study suitable for:
Students who are interested in learning what big data is or who could benefit from big data processing techniques in their work.
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This course is included in the following theme