5 ECTS credits

English

Period IV. It is recommended that the course is taken on the fourth year Spring.

Upon completion of the course, the student :

1. is able to explain the big data phenomenon, its challenges and opportunities.
2. 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.
3. can explain the principles of big data management and processing technologies and utilize them on a basic level.

General introduction into big data, namely: big data fundatmenals, data storage, batch and stream data processing, data analysis, privacy and security, big data use cases.

Face-to-face teaching, independent and group work

Lectures, exercises, seminars, independent and group work

M.Sc. students (computer science and engineering) and other Students of the University of Oulu

The Bachelor level studies of Computer science and engineering study programmes or respective knowledge.

Finishing 521290S Distributed Systems, 521497S Pattern recognition and neural networks, and 521286A Computer Systems is beneficial.

Lecture slides and exercise material will be provided. Each lecture will include the refernce list for recommended reading. Instructions to necessary installations will be given.

This course assesses students continuously by the completion of exercises, seminar presentations and short reports on a selected topic (group work), and answering two quizzes during the course. To pass the course, it is enough to get 50 % of available points. No exam.

Read more about assessment criteria at the University of Oulu webpage.

The course utilizes a numerical grading scale 1-5. In the numerical scale zero stands for a fail.

Ekaterina Gilman

The course includes also invited lectures from industry.