Data Science and Big Data FundamentalsLaajuus (5 ECTS)

Objective

The target of the course is to provide understanding of the capabilities of big data and data science
methods. The participants get hands-on experience in storage, retrieval, and analysis of big data and tools for analysis, and complete a project where these are used.

Content

• Big Data in ICT business: applicability, opportunities, models and processes, legal and ethical
constraints.
• Acquisition and preprocessing of data, Open data. interfaces to data.
• Data management solutions (RDBMS, No-SQL, other data models), Hadoop , MapReduce and
distribution of workload.
• Analysis of big data: data mining methods (association analysis, clustering, classification), text and
web mining, analysis tools, visualization and communication of analysis outcomes.

Qualifications

No formal requirements. Data management and mathematics skills will be helpful in acquiring the
contents of the course.

Assessment criteria, satisfactory (1)

The student has achieved the course objectives fairly. The student will be able to identify, define and use the course subject area’s concepts and models. The student has completed the required learning exercises in minimum requirement level. His/her competences have developed in a way that he/she may increase his/her knowledge in the given field and finally work in a suitable job position related to this field.

Assessment criteria, approved/failed

The student has achieved the course objectives fairly. The student will be able to identify, define and use the course subject area’s concepts and models. The student has completed the required learning exercises in minimum requirement level. His/her competences have developed in a way that he/she may increase his/her knowledge in the given field and finally work in a suitable job position related to this field.