Program Overview

Program Overview

The University of Copenhagen offers a comprehensive range of academic programs, including Bachelor's, Master's, PhD, and Continuing Education courses. The programs are designed to provide students with a thorough understanding of their chosen field, as well as the skills and knowledge necessary to succeed in their future careers.

Bachelor's Programs

The University of Copenhagen offers several Bachelor's programs, including:

• BSc Programme in Bioinformatics
• BSc Programme in Computer Science and Economics
• BSc Programme in Computer Science
• BSc Programme in Machine Learning and Data Science

Course Description

The course NDAB21010U Databases and Information Systems (DIS) is a 7.5 ECTS course that introduces students to basic database concepts, system development, and version control. The course covers topics such as:

• Relational databases
• Normal forms
• Transactions
• Entity-relationship modeling
• Relational data modeling
• Queries in database query languages
• Database normalization
• ACID properties
• Indexing techniques
• Use of constraints and triggers
• Facilities for connecting databases, programming environments, and program libraries
• Methods for reading structured texts

Learning Outcomes

Upon completion of the course, students will have gained:

• Knowledge of key database technical concepts
• Skills in developing a data model and realizing database applications
• Competence in developing a database design and implementing database applications
• Competence in effectively participating in an agile software development process

Literature

The course literature will be available on Absalon when the course is set up.

Recommended Academic Qualifications

Students are expected to have programming skills and experience in software development at a level corresponding to the completion of the DIKU courses "Programming og problemløsning" and either "High Performance Programming and Systems" or "Computer Systems".

Teaching and Learning Methods

The course will be taught through a combination of lectures, exercise sessions, and a practical group project.

Workload

The course workload is estimated to be:

• Lectures: 28 hours
• Preparation: 78 hours
• Exercises: 14 hours
• Project work: 82 hours
• Exam: 4 hours
• Total: 206 hours

Exam

The exam is an on-site written exam, 4 hours under invigilation. The exam is an ITX exam, and students are allowed to bring all aids except Generative AI and internet access.

Examination Prerequisites

To be eligible for the exam, students must have:

• Approved the group project
• Passed two mandatory assignments, marked as pass/fail

Marking Scale

The exam will be marked on a 7-point grading scale.

Re-exam

The re-exam will be a 4-hour written test with written aids. If there are 10 or fewer students registered, the re-exam will be changed to an oral exam (30 min. including voting) without preparation.

Course Information

• Language: English
• Course code: NDAB21010U
• Credit: 7.5 ECTS
• Level: Bachelor
• Duration: 1 block
• Placement: Block 4
• Schedule: A
• Course capacity: No limitation – unless you register in the late-registration period (BSc and MSc) or as a credit or single subject student.

Study Board

The study board responsible for the course is the Study Board of Mathematics and Computer Science.

Contracting Department

The contracting department is the Department of Computer Science.

Contracting Faculty

The contracting faculty is the Faculty of Science.

Course Coordinators

The course coordinators are Dmitriy Traytel.