The course is included in these curricula and study modules
- Information technology 2014 - Analytical methods and data science
- Information technology 2015 - Analytical methods and data science
- Information technology 2016 - Analytical methods and data science
- Information technology 2017 - Analytical methods and data science
- Information technology 2018 - Data processing and applied mathematics & physics
- Information technology 2019 - Data processing and applied mathematics & physics
- Information technology 2020 - Data processing and applied mathematics & physics
- Information technology 2021 - Information, data and applied mathematics & physics - foundation studies
- Information technology 2022 - Information, data and applied mathematics & physics - foundation studies
- Information technology 2023 - Information, data and applied mathematics & physics - foundation studies
The course takes place in period
3 (2024-01-01 to 2024-03-17)
Level/category
Teaching language
Swedish
Type of course
Compulsory
Cycle/level of course
First
Recommended year of study
2
Total number of ECTS
5 cr
Competency aims
In this study unit the focus lies on the following
competencies:
Data structures and algorithms.
Object-oriented programmning
SDG's in focus:
#9 Industry, innovation and infrastructure
Learning outcomes
Upon completion of this study unit:
You understand how different data structures can
be used for data storage and processing.
(Knowledge)
You understand the basic concepts of object-
oriented programming. (Knowledge)
You understand and can implement basic data
structures and algorithms. (Skills)
You can develop larger object-oriented projects in
Java. (Skills)
You can utilize your understanding data structures
and algorithms in general programming problem.
(Approach)
You see the OOP principles as tools to be used for
extensive programming projects. (Approach)
Course contents
Repetition and deepening
- object-oriented programming in Java
- OOP-concepts such as inheritance, abstraction,
encapsulation, polymorphism
Algorithms
- the algorithm concept
- structuring (sub-algorithms, recursion)
- complexity
- examples of algorithms (including linear data
structures, search, sort)
Data structures
- dynamic data structures
- linear data structures (stack and queue)
- linked data structures (lists, trees and
graphs)
- hash tables
The data type concept
- primitive types
- enumerated types
- structured types
Prerequisites and co-requisites
Mathematical programming
Statistics and probability
Study activities
- Lectures - 40 hours
- Project- and production work/artistic activities - 95 hours
Workload
- Total workload of the course: 135 hours
- Of which autonomous studies: 135 hours
- Of which scheduled studies: 0 hours
Mode of Delivery
Participation in tuition
Assessment methods
Assessment requirements
The course is graded based on programming
projects, quizzes and exercises.
Teacher
Welander Fredrik
Examiner
Welander Fredrik
Home page of the course
Group size
No limit
Assignments valid until
12 months after course has ended
The timetable of the course
Se Itslearning.
Course enrolment period
2023-11-24 to 2023-12-22
Assessment methods
Date will be announced later - Other assignments