Master's Programme in Data Science is responsible for the course.
The course belongs to the CSM14000 - Software Systems study track module.
The course is available to students from other degree programmes.
Prerequisites in terms of knowledge
Good programming skills. Basic data models such as the relational data model and semi-structured data models (e.g., JSON, XML).
Prerequisites for students in the Data Science programme, in terms of courses
Prerequisites for other students in terms of courses
TKT10002 Introduction to Programming
Recommended preceding courses
- Transaction management and query optimisation
- Big data framework
- Distributed data framework
Recommended time/stage of studies for completion: autumn the first or second year of the Master study
Term/teaching period when the course will be offered: the course is in Autumn term / second period. The course will be offered every year.
- Hadoop and MapReduce, HDFS
- data models, relational databases and SQL
- semi-structured data and JSON query with MongoDB
- data streaming and data lake
- data integration
- Hands-on experience for different systems, including Splunk, Hadoop, Gephi, PostgreSQL and MongoDB.
The grading is based on the sum of the points from the exercises (max. 50 marks) and the exam (max. 50 marks). 51 marks are required to pass and give the lowest grade 1, 91 points or more gives the highest grade 5.
General exams last 3 hours and 30 minutes. Renewal exam (marked with "(U)") is the first general exam after the course and also a renewal exam of course exam(s). In a renewal exam the points student has earned during the course are taken into account. Exams marked with "(HT)" are allowed only to students who have completed the obligatory projects or other exercises included in those courses. Exams marked with "(HT/U)" are renewals to students who have completed the obligatory projects during the course. General exams might cover different area than the lectured course. Check the course web page and contact the responsible teacher if in doubt.