Advanced Topics in Big Data

6 ECTS credits
176 h study time

Offer 1 with catalog number 4023256FNR for all students in the 2nd semester at a (F) Master - specialised level.

Semester

2nd semester

Enrollment based on exam contract

Impossible

Grading method

Grading (scale from 0 to 20)

Can retake in second session

Enrollment Requirements

Students who want to enroll for this course, must have passed or be enrolled in Scalable Analytics and Information Visualisation.

Taught in

English

Faculty

Faculty of Sciences and Bioengineering Sciences

Department

Computer Science

Educational team

Bas Ketsman
Beat Signer (course titular)

Activities and contact hours

12 contact hours Lecture
24 contact hours Seminar, Exercises or Practicals
156 contact hours Independent or External Form of Study

Course Content

In this seminar the students get insights about recent developments in the field of Big Data systems. They will deepen their knowledge about specific research topics in this domain. This course is based on interactive sessions where students have discussions with the professors. As a base line, students study scientific papers which need to be read before each session in order to facilitate a discussion. A list of themes with associated research papers is put forward each year and, for instance the following topics might be covered:

Scalable data management systems
Distributed query processing
Coordination-free querying
Big data analytics
Scalable architectures
Graph processing
Privacy preservation on big data
Human-in-the-loop data processing
Human-data interaction
Data physicalisation
Personal information management
Information visualisation
Advanced data processing UIs

Each student is assigned one theme based on their interest. The student must critically review the assigned research papers, identify the main contributions and synthesise the theme for peers in a presentation. All students contribute to the discussion.

Next to that, each student must write a review of an assigned research paper in a provided review format that is similar to review formats used at main research conferences in the associated domains.

The study material is composed based on the selected subjects. Due to the interactive nature of the course, the student is obliged to be present during the contact hours. Therefore the course cannot be taken with an exam contract and it is not possible to take an exam in second session.

Course material

Digital course material (Required) : Additional information (such as schedules, teaching assistants, contact information, deadlines, assignments etc.) might be found on the learning platform., Learning platform

Additional info

The lectures are given in English.

Attending the lectures is mandatory. The assigned research papers will be provided to the students. Additional information in the form of related work and cited papers will have to be collected by the students.

Additional information (such as schedules, teaching assistants, contact information, deadlines, assignments etc.) might be found on the learning platform.

Learning Outcomes

General competencies

Knowledge and Insight:
In this seminar the student gets insights about recent developments in the field of Big Data systems. They will deepen their knowledge about specific topics in Big Data systems and are required to communicate the outcome to other course participants. The student should be able to critically review the assigned research papers, identify the main contributions and communicate the content in the form of a presentation as well as in a written report.

Application of Knowledge and Insight:
Since this course is given in a seminar form that is mainly based on the study of research papers, the students will not apply the acquired scientific knowledge in an exercise or project-specific form. However, they apply new insights about the independent investigation of a research topic as well as different forms of presentation as part of their assignment.

Judgement Shaping:
The student is required to identify the contributions as well as strengths and weaknesses of a given research paper. They should further get an insight of how evaluate and position a research paper in the context of related work.

Communication:
As part of the seminar the student is required to clearly communicate about the assigned research topic. The attendee shows that they can reflect on a given research topic and discuss it with colleagues by asking and answering scientific questions.

Learning Skills:
After having attended this course, the student has the necessary knowledge to independently investigate a given research topic based on specific research papers and other resources.

The course contributes to the following learning outcomes of the Master's programme:

The Master has in-depth and active knowledge of the academic literature of advanced concepts from the chosen specialisation.
The Master can report and communicate scientifically in English, orally and in writing, to an audience of peers.
The Master has a research attitude, can process scientific and technical information independently, and can acquire lacking knowledge quickly.
The Master behaves responsible, can cope with work-related pressure, is disciplined and precise in executing assignments and all of this both in independent work and in a teamwork.

Grading

The final grade is composed based on the following categories:
LEC Presentation determines 70% of the final mark.
PRAC Paper determines 30% of the final mark.

Within the LEC Presentation category, the following assignments need to be completed:

Presentation of a topic/paper with a relative weight of 100 which comprises 70% of the final mark.

Within the PRAC Paper category, the following assignments need to be completed:

Report and reviews with a relative weight of 100 which comprises 30% of the final mark.

Additional info regarding evaluation

The final grade is going to be based on the student's presentation (counts for 70% of the final grade) as well as on the written report and the review of a number of additional papers (counts for 30% of the final grade). Note that the attendance of the lectures/presentations is mandatory and an unjustified absence (i.e without medical or other certificate) from more than three lectures in total will result in the grade 'absent' for the seminar.

Allowed unsatisfactory mark

The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context