General Information
| Course Code | X_401008 |
|---|---|
| Credits | 6 EC |
| Period | P5 |
| Course Level | 200 |
| Language of Tuition | English |
| Faculty | Faculty of Science |
| Course Coordinator | dr. J. Endrullis |
| Examiner | dr. J. Endrullis |
| Teaching Staff |
dr. J. Endrullis |
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Part of programme(s)
Premaster
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Practical Information
You need to register for this course yourself. The (de)registration deadlines can be found on VU.nl
| Teaching Methods | Computer lab, Practical, Lecture |
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Target audiences
This course is also available as:
Course Objective
The students will learn:
- to design and evaluate database schemas using Entity-Relationship diagrams, (Applying knowledge and understanding) (Making judgements)
- to understand the relational model (including integrity constraints such as key constraints and foreign key constraints), (Knowledge and understanding)
- to translate Entity-Relationship diagrams into relational schemas (and to enforce cardinality constraints by design), (Applying knowledge and understanding)
- to reason about good and bad database design using functional dependencies, (Making judgements)
- to apply normalization algorithms to transform a database schema into (various) normal forms, (Applying knowledge and understanding)
- to understand concurrency concepts like transactions, schedules and concurrency anomalies, and (Knowledge and understanding)
- to reason about different techniques for concurrency control (lock based concurrency control, optimistic concurrency control, multiversion concurrency control). (Making judgements)
Course Content
The course is concerned with base principles and important aspects of relational databases. The course objective is to obtain a good knowledge and understanding of relational database systems. This includes the ability to develop good database models, and to query and update databases using SQL.
Additional Information Teaching Methods
Lectures, exercise/practicum classes and individual homework.
The assessment in this course is bases on a digital final exam. It follows a No AI policy. That is, the assessment is completed entirely without AI assistance in a controlled environment, ensuring that students rely solely on their existing knowledge, understanding, and skills. The homework assignments are not in a controlled environment. Nevertheless, we expect that the homework solutions are your own work and not generated with AI. However, you may freely use AI for studying and learning the concepts of this course.
Method of Assessment
The homework is mandatory for qualifying for the exam (70% of the homework points to qualify for the exam). In the case that at least 90% of the homework points are obtained, 0.5 bonus points are awarded for the final grade. At the end of the course, there is a final exam.
The overall grade is the grade of the final exam plus the possibly 0.5 bonus point obtained for the homework. (The bonus is only added for students who pass the exam with a grade of at least 5.5.)
There is no resit opportunity for the homework.
Literature
Database Systems, The Complete Book, by: Hector Garcia-Molina & Jeffrey D. Ullman & Jennifer Widom. 2nd edition.
Additional Information Target Audience
Bachelor Artificial Intelligence (year 2)Bachelor Business Analytics (year 2)
Bachelor Computer Science (year 2)