DM573: Introduction to Computer Science

Study Board of Science

Teaching language: Danish or English depending on the teacher
EKA: N330056102
Assessment: Second examiner: Internal
Grading: 7-point grading scale
Offered in: Odense
Offered in: Autumn
Level: Bachelor

STADS ID (UVA): N330056101
ECTS value: 7.5

Date of Approval: 05-02-2022


Duration: 1 semester

Version: Approved - active

Comment


Entry requirements

This course cannot be taken by students who have passed DM534 or DM558.

Academic preconditions

Students following the course are expected to acquire knowledge of basic discrete mathematics and competences in basic programming concurrently with the course (or earlier).

Course introduction

One goal of the course is to give a brief introduction to a broad selection of topics within computer science, such that the student early in his/her education gets a feel for the nature of the subject and the characteristics of the education. A second goal is to increase awareness of the importance of understanding when working with course material.

The course partially builds on the knowledge acquired concurrently in the courses DM574 Introduction to Programming and DM549 Discrete Methods for Computer Science and constitute a perspectivizing foundation for the rest of the education in computer science.

In relation to the qualifications profile of the education, the course has explicit focus on the ability to:

  • Understand and reflect upon theories, methods, and practice in the realm of computer science.
  • Make and justify professional decisions.

Expected learning outcome

To achieve the goal of the course, its expected learning outcome is that the student demonstrates the ability to:

  • Convert numbers from decimal to binary or floating point representation, and back.
  • Construct simple logical circuits.
  • Program in a simplified machine language.
  • Perform simple data modeling and simple queries in a relational database.
  • Design and implement simple algorithms and analyze their properties, including correctness and running time.
  • Describe the idea of RSA-encryption and perform related calculations.
  • Describe and apply some principles from artificial intelligence.
  • Solve simple problems concerning finite automata, context-free grammars, and regular expressions.
  • Model and solve combinatorial problems with SAT-solvers.

Content

The course contains the following main topics:

  • History of computer science
  • Computer architecture
  • Algorithms
  • Databases
  • Finite automata, context-free grammars, and regular expressions
  • Modeling and solving combinatorial problems with SAT-solvers
  • Artificial intelligence
  • Cryptology
  • 3D graphics

Literature

See itslearning for syllabus lists and additional literature references.

Examination regulations

Exam element a)

Timing

Autumn

Tests

Mandatory assingments

EKA

N330056102

Assessment

Second examiner: Internal

Grading

7-point grading scale

Identification

Full name and SDU username

Language

Normally, the same as teaching language

Examination aids

To be announced during the course

ECTS value

7.5

Additional information

Mandatory assignments in the form of multiple choice tests made during the course.
Re-examination in the same period or immediately thereafter.
The re-examination is an oral examination assessed by 7-point grading scale and internal co-examination.

Indicative number of lessons

84 hours per semester

Teaching Method

At the faculty of science, teaching is organized after the three-phase model ie. intro, training and study phase.
  • Intro phase: 56 hours
  • Training phase: 28 hours, of which 28 hours exercise classes and 0 hours lab
  • Study phase: 45 hours
In the intro phase a modified version of the classical lecture is employed, where the terms and concepts of the topic are presented, from theory as well as from examples based on actual data. In these hours there is room for questions and discussions. In the training phase the students work with data-based problems and discussion topics, related to the content of the previous lectures in the intro phase. In these hours there is a possibility of working specifically with selected difficult concepts. In the study phase the students work independently with problems and the understanding of the terms and concepts of the topic. Questions from the study phase can afterwards be presented in either the intro phase hours or the training phase hours.
 
Activities during the study phase:
  • Solve assignments
  • Read the assigned literature
  • Practice to apply the acquired knowledge

Teacher responsible

Name E-mail Department
Rolf Fagerberg rolf@imada.sdu.dk Algoritmer

Timetable

Administrative Unit

Institut for Matematik og Datalogi (datalogi)

Team at Educational Law & Registration

NAT

Offered in

Odense

Recommended course of study

Transition rules

Transitional arrangements describe how a course replaces another course when changes are made to the course of study. 
If a transitional arrangement has been made for a course, it will be stated in the list. 
See transitional arrangements for all courses at the Faculty of Science.