Course

Algorithms and Datastructures (DAT200)

The course provides an in-depth introduction to some commonly used data structures and algorithms.


Dette er emnebeskrivelsen for studieåret 2020-2021. Merk at det kan komme endringer.

See course description and exam/assesment information for this semester (2024-2025)

Semesters

Fakta

Emnekode

DAT200

Vekting (stp)

10

Semester undervisningsstart

Autumn

Undervisningsspråk

English

Antall semestre

1

Vurderingssemester

Autumn

Timeplan

Vis timeplan

Litteratur

Pensumlisten finner du i Leganto

Content

Algorithm efficiency analysis. Definition, usage, and implementations of abstract data types: Stacks, queues, lists, associative arrays (dictionary in Python), tree structures, graphs, priority queues, heaps. Hash techniques. Tree structures. Implementation and use of data structures that can represent graphs. Algorithms for sorting and searching. Some basic algorithms for graphs, including wayfinding. Use of recursion as programming technique.

Learning outcome

After ending this course the student should know how to:

Knowledge

  • Know how basic algorithms for sorting, searching and wayfinding in graphs work.
  • Know how basic data structures for lists, stacks, queues, priority queues, sets, associative arrays and graphs work

Skills

  • Be able to calculate the efficiency of algorithms
  • Be able to implement efficient recursive algorithms
  • Be able to implement efficient algorithms for sorting and searching

General competency

  • Know how data structures and algorithms for lists, queues, stacks, heaps, binary trees and graphs can be implemented.
  • Be able to use standard algorithms and data structures to implement efficient programs

Forkunnskapskrav

The student is expected to know how to program at a level equivalent to DAT110 Introduction to programming.

Anbefalte forkunnskaper

Object-oriented Programming (DAT100), Introduction to Programming (DAT110)

Exam

Form of assessment Weight Duration Marks Aid Exam system Withdrawal deadline Exam date
Home exam 1/1 4 Hours Letter grades — 20.11.2020 —


This course has digital exam. It will be possible to use Scantron to scan drawings made by hand and connect these to the digital exam.

Vilkår for å gå opp til eksamen/vurdering

Hand-in assignments, Hand-in assignments
There are nine exercises in this course. In order to be allowed to take the exam at least seven out of the nine exercises need to be approved within the given deadline.

Fagperson(er)

Head of Department:

Tom Ryen

Course coordinator:

Mina Farmanbar

Method of work

Six hours of lecturing per week. All students can get help for the exercises at a room reserved for the purpose four hours a week. The exercises are approved by presenting them to the teacher or a student assistant during these four hours.

Completion of mandatory exercises are to be made at the times and in the groups that are assigned and published. Absence due to illness or for other reasons must be communicated as soon as possible to the laboratory personnel. One cannot expect that provisions for completion of the exercises at other times are made unless prior arrangements with the laboratory personnel have been agreed upon.

Failure to complete the assigned exercises on time or not having them approved will result in barring from taking the exam of the course.

Overlapping

Emne Reduksjon (SP)
Algorithms and Datastructures (DAT200_1) , Data structures and algoritms (TE0458_1) 6
Algorithms and Datastructures (DAT200_1) , Data structures and algoritms (TE0458_A) 6
Datastructures and algorithms (BIE270_1) , Algorithms and Datastructures (DAT200_1) 10

Åpent for

Battery and Energy Engineering - Bachelor in Engineering Civil Engineering - Bachelor in Engineering Computer Science - Bachelor in Engineering Computer Science - Bachelor in Engineering, Part-Time Electrical Engineering - Bachelor's Degree Programme, part-time Electrical Engineering - Bachelor's Degree Programme Energy and Petroleum Engineering - Bachelor in Engineering Geosciences and Energy Resources - Bachelor in Engineering Environmental Engineering - Bachelor in Engineering Mechanical Engineering - Bachelor in Engineering Medical technology - Bachelor in Engineering Medical Technology - Bachelor in Engineering - part time
Admission to Single Courses at the Faculty of Science and Technology
Industrial Economics - Master of Science Degree Programme, Five Year Industrial Automation and Signal Processing - Master's Degree Programme - 5 year

Emneevaluering

Form and/or discussion.

Litteratur

Pensum1. Miller BN. Problem solving with algorithms and data structures using Python. (Ranum DL, red.). Franklin, Beedle & Associates; 2006:XI, 357. https://runestone.academy/runestone/books/published/pythonds/index.html2. Kompendium.3. Øvingsoppgaver.Alternativ litteratur4. Cormen TH. Introduction to algorithms . Third edition. (Stein C, Rivest R, Leiserson CE, Cormen TH, red.). MIT Press; 2009.

Kontakt

Head of Department:

Tom Ryen

Course coordinator:

Mina Farmanbar

Tilbys av

Faculty of Science and Technology

Department of Electrical Engineering and Computer Science

The course description is retrieved from FS (Felles studentsystem). Version 1