Curriculum

The elective: Big Data Workshop

Contents

This course is intended to qualify the student to:

• Analyse, Design and Implementation of Big Data .

ECTS credits

10 ECTS

Learnings objectives

Knowledge

The student has knowledge about:

1. the theory and practice of the Big Data topic
2. understand the concepts of Volume, Variety, Velocity, Variability, Veracity and Complexity for Big Data..
3. understand Big Data as data driven business (e.g. new combination of data to provide new services)

Skills

The student can:

1. select, describe and search for literature concerning a problem of his/her own choice within the context of information technology
2. discuss relevant processes and analytical approaches associated with the Big Data i.e. maintaining Big Data problems and develope a solution, this could be from analyzing sociel medias
3. communicate key results.
4. be able to set up a small experiment using techniques and tools from Big Data (mostly Hadoop) e.g. databases, deduce new knowledge, some kind of artificial intelligence

Competences

The student can:

1. familiarise himself/herself with Big Data in the context of the theory and/or practices of the discipline without the assistance of others
2. put the chosen topic(s) into a wide perspective and relate it/them to the other topics addressed during the programme.
3. reflect on different uses of Big Data for solving the business of tomorrow.

Assessment

This course is a part the exams after the 4th semester.
During the course the student must hand in mandatory assignments. Mandatory assignments must be passed before the exam.

If possible a company will provide a case study to be the base of the mandatory assignment.

Technologies

The elective educational elements give the student an opportunity to enhance his/her academic and professional
competence by specialising and putting themes into perspective within the wider scope of Big Data with a special focus on Hadoop.