6 ECTS credits
150 h study time
Offer 2 with catalog number 4023868FNW for working students in the 1st semester
at
a (F) Master - specialised level.
- Semester
- 1st semester
- Enrollment based on exam contract
- Impossible
- Grading method
- Grading (scale from 0 to 20)
- Can retake in second session
- Yes
- Enrollment Requirements
- Following courses are mutually exclusive: 'Open Informatiesystemen' and 'Open Information Systems'
- Taught in
- English
- Faculty
- Faculty of Sciences and Bioengineering Sciences
- Department
- Computer Science
- Educational team
- Bas Ketsman
(course titular)
- Activities and contact hours
- 26 contact hours Lecture
26 contact hours Seminar, Exercises or Practicals
- Course Content
In this course, we study principles of data and information systems. Topics include data models and query languages, properties of queries, algorithms and techniques for query processing, optimization, and data integration and interoperability.
- Course material
- Digital course material (Required) : Relevant material (including the lecture slides), lecture slides, additional papers and book chapters, contact information, deadlines, exercises, exam details, Learning platform
- Additional info
The lectures are given in English. Relevant course material (slides) is available on the learning platform. For specific course topics, pointers to relevant additional resources (research papers, books and book chapters, website, specifications, online tutorials etc.) will be provided as well.
- Learning Outcomes
-
Algemene competenties
By the end of the course, the student will be able to:
- Explain and relate to each other different data models, query languages and their trade-offs.
- Understand the fundamental principles underlying query languages and their different perspectives.
- Understand the effect of properties of queries and query languages on their computational complexity.
- Understand the relationship between techniques for query processing, reasoning and data integration.
- Independently apply and implement any of the discussed algorithms and techniques for query optimization and processing.
- Design and motivate data layouts, algorithms, query plans and optimization techniques for specific query workloads.
- Analyze the trade-offs for algorithms and techniques in the context of specific query workloads.
- Recognize variations and combinations of techniques and algorithms in the field of data and information management.
- Evaluate the applicability of a given technique or algorithm in a specific data and information system context.
- Report verbally and in writing about topics in the field of data and information systems and answer questions about them.
- Independently continue the study of data and information management systems and techniques.
- Grading
-
The final grade is composed based on the following categories:
Written Exam determines 60% of the final mark.
PRAC Teamwork determines 40% of the final mark.
Within the Written Exam category, the following assignments need to be completed:
- Oral exam
with a relative weight of 1
which comprises 60% of the final mark.
Within the PRAC Teamwork category, the following assignments need to be completed:
- Project
with a relative weight of 1
which comprises 40% of the final mark.
- Additional info regarding evaluation
The final grade is a weighted average. During the semester an assignment has to be done (counts for 40% of the final grade). During the exam period a written exam (counts for 60%) covering all the course topics will be conducted. In order to pass the course, the final grade has to be at least 10/20. Furthermore, each individual grade (assignment or exam) has to be at least 8/20, otherwise the lowest of these two grades becomes the final grade. In the second exam period, assignments that were not satisfactory can be reworked and defended again. Also the written exam can be redone. The final mark is calculated in the same way as in the first exam period.
- 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
This offer is part of the following study plans:
Master of Applied Sciences and Engineering: Computer Science: Artificial Intelligence
Master of Applied Sciences and Engineering: Computer Science: Multimedia
Master of Applied Sciences and Engineering: Computer Science: Software Languages and Software Engineering
Master of Applied Sciences and Engineering: Computer Science: Multimedia for Northwestern Polytechnical University (NPU)
Master of Applied Sciences and Engineering: Computer Science: Data Management and Analytics