Algorithms and Data Structures

2023/2024

Content, progress and pedagogy of the module

Disclaimer.
This is an English translation of the module. In case of discrepancy between the translation and the Danish version, the Danish version of the module is valid.

Learning objectives

Knowledge

The student must gain knowledge of the following theories and methods:

  • Mathematical basic concepts such as recursion, induction, concrete and abstract complexity  
     
  • internal and external data structures, algorithm principles such as search, search trees, internal and external sorting, dynamic programming, part-and-intake  
     
  • Graphs and graph algorithms such as shortest road, consistency components, unfolding tree

Skills

  • Determine abstract complexity for concrete features implement complexity and correctness analysis on simple algorithms, including recursive algorithms  
     
  • Select and use appropriate algorithms for standard tasks, such as search, sorting and finding

Competences

The student must, faced with a non-standard programming task, be able to

  • Develop algorithms and data structures to solve the task
     
  • Analyze the developed algorithms

Type of instruction

The training shall be organised according to the general teaching forms referred to in § 17

Extent and expected workload

The student is expected to spend 27.5 hours per ECTS, which for this activity means 137.5 hours.

Exam

Exams

Name of examAlgorithms and Data Structures
Type of exam
Written or oral exam
ECTS5
Assessment7-point grading scale
Type of gradingExternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Facts about the module

Danish titleAlgoritmer og datastrukturer
Module codeDSNDATFB211
Module typeCourse
Duration1 semester
SemesterSpring
ECTS5
Language of instructionEnglish
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module

Organisation

Education ownerBachelor of Science (BSc) in Data Science and Machine Learning
Study BoardStudy Board of Computer Science
DepartmentDepartment of Computer Science
FacultyThe Technical Faculty of IT and Design