DM536: Introduction to Programming

Study Board of Science

Teaching language: Danish or English depending on the teacher, but English if international students are enrolled
EKA: N330004102
Assessment: Second examiner: Internal
Grading: 7-point grading scale
Offered in: Odense
Offered in: Autumn
Level: Bachelor

STADS ID (UVA): N330004101
ECTS value: 5

Date of Approval: 31-03-2022


Duration: 1 semester

Version: Approved - active

Comment

Co-read with the first nine weeks of DM574.

Entry requirements

The course cannot be followed if the student has passed DM550, DM562, DM574, DM857, DS800, DS801, DS830 or MM560, or if the student has DM550, DM562, DM857, DS800, DS801, DS830 or MM560 mandatory in their curriculum.

Academic preconditions

None

Course introduction

The course gives an introduction to structured programming.  The course provides an academic basis for solving problems by modelling and implementing computer programs.

In relation to the learning outcomes of the degree the course has explicit focus on:
  • implement the use of computers in practice
This course builds upon the students' highschool competences in Mathematics. The course's content is essential for later courses in algorithms and software development, where the students are required to be able to program, in particular Scientific Programming.

Expected learning outcome

The learning objectives of the course are that the student demonstrates the ability to:
  • design models for concrete problems.
  • devise a program structure based on the model.
  • implement the planned program in the concrete programming language used.
  • design and implement recursive solutions of problems.
  • use basic tree structures and algorithms for these.

Content

The following main topics are contained in the course:

  • The basic structuring tools sequence, repetition, conditional instruction and procedure.
  • Fundamental data structures such as lists, maps, and trees.
  • Structured programming techniques, including examples and applications.
  • Recursion and recursive data structures.

The course is taught in Python.

Literature

See itslearning for syllabus lists and additional literature references.

Examination regulations

Exam element a)

Timing

Autumn and January

Tests

Portfolio examination with oral defence

EKA

N330004102

Assessment

Second examiner: Internal

Grading

7-point grading scale

Identification

Full name and SDU username

Language

Normally, the same as teaching language

Duration

Oral examination 30 minuttes

Examination aids

All allowed. - the project
Not allowed - oral defence.

ECTS value

5

Additional information

Portfolio consisting of: The exam consists of a group project (programming and written report), possibly divided into several submissions. The oral defence is held during the exam period in january. The defence takes form as a group exam, taking into account each student's individual contribution. In addition, there are some small compulsory (individual) assignments that need to be solved in some selected e-hours during the course of the semester.

Indicative number of lessons

40 hours per semester

Teaching Method

At the faculty of science, teaching is organized after the three-phase model ie. intro, training and study phase.
Teaching activities are planned for the following amount of hours:

  • Introphase (lectures): 20 hours
  • Training phase: 20 hours (discussions)
In the intro phase a combination of classical lectures, where the terms and methods of the course are presented, and more applied sessions, where students are taught how the learnt knowledge can be applied in concrete scenarios, is employed.

The training phase consists of discussion sessions, where the students learn the competences that enable them to transform their knowledge into solution and, consequently, into concrete computer programs.

In the study phase the students get concrete problems to solve in small groups, with the goal of improving their understanding and their competences regarding the contents of the course.

Teacher responsible

Name E-mail Department
Luís Cruz-Filipe lcf@imada.sdu.dk Concurrency

Timetable

Administrative Unit

Institut for Matematik og Datalogi (datalogi)

Team at Educational Law & Registration

NAT

Offered in

Odense

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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.