5 ECTS credits
|Language of instruction
Period IV. It is recommended that the course is taken on the fourth year Spring.
Upon completion of the course, the student :
- is able to explain the big data phenomenon, its challenges and opportunities.
- 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.
- 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.
|Mode of delivery
Face-to-face teaching, independent and group work
|Learning activities and teaching methods
Lectures, exercises, seminars, independent and group work
M.Sc. students (computer science and engineering) and other Students of the University of Oulu
|Prerequisites and co-requisites
The Bachelor level studies of Computer science and engineering study programmes or respective knowledge, the exercises do not require programming skills but they are an advantage.
|Recommended optional programme components
Finishing 521290S Distributed Systems, 521497S Pattern recognition and neural networks, and 521286A Computer Systems is beneficial.
|Recommended or required reading
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.
|Assessment methods and criteria
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 for each part. 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.
|Working life cooperation
The course includes also invited lectures from industry.