Study plan for MAMN-INFAG Algorithms, fall 2024
Name of qualification
Master of Science in Informatics - Algorithms
ECTS Credits
Two years of full-time study, where the normal workload for a full-time student is 60 credits for one academic year.
Full-time/Part-time
Full-time
Language of Instruction
English
Semester
For applicants residing in Norway: autumn and spring
Objectives and content
A Master's degree in informatics with a specialization in algorithms has a focus on the development and improvements of algorithms and computer programs, so that problems and challenges can be solved in the best and fastest way on computers. The aim is to find the best and most effective methodology, either through analysis, or through practical testing.
This Master's degree programme also includes fundamental aspects of algorithms, such as identification of problems that are hard to solve on computers. In these situations, development of alternative solutions is the main focus.
Required Learning Outcomes
A candidate who has completed his or her qualification should have the following learning outcomes defined in terms of knowledge skills and general competence:
Knowledge:
The candidate
- Can analyze code and algorithms
- Can implement algorithms
- Can assess the suitability of an algorithm
- Can develop efficient algorithms for problems that can be solved in polynomial time
- Can use techniques to handle difficult problems
Skills:
The candidate
- Can analyze code and algorithms to find bottlenecks, and then know how to handle them.
- Can implement algorithms rapidly and efficiently.
- Can decide if a given algorithm is suitable for its intended purpose.
- Can distinguish between problems that can and those that most likely cannot be solved in polynomial time.
- Can develop efficient algorithms for problems that can be solved in polynomial time.
- Can use the most common techniques for handling difficult problems.
General competence:
The candidate
- Is able to work independently and in groups with others.
- Has a critical and analytical view of his/her own work and that of others.
- Is able to evaluate ethical aspects of his/her own projects.
Admission Requirements
The master's programme builds on a bachelor's degree from the Department of Informatics, or a bachelor's degree and at least 80 ECTS of Mathematics and Informatics/Computer science.
Bachelor's degrees from UiB that qualify:
- Bachelor's degree from Department of Informatics, UiB (BAMN-BINF, BAMN-DSIK, BAMN-DTEK, BAMN-DVIT, BATF-IMØ, BAMN-INF)
- Bachelor's degree in Information and Communication Technology (IKT) with at least 15 ECTS (at least two courses for at least 7,5 ECTS each) of elective Mathematics
- Bachelor's degree in Cognitive Science (BASV-KOGNI) with specialization in Informatics
- Bachelor's degree in Artificial Intelligence (BASV-AIKI) qualifies, if you have at least 80 ECTS of Mathematics and Informatics/Computer Science. Out of these 80 ECTS, at least 40 ECTS must be in Informatics/Computer science, and at least 15 ECTS must be in Mathematics. One course in Statistics can count towards Mathematics (except STAT100). MNF130 and equivalent counts as Informatics. INF-courses and INFO-courses with credit reduction towards INF-courses count as informatics.
Bachelor's degrees that qualify
- Bachelor's degree in Computing from HVL (Western Norway University of Applied Sciences)
- Bachelor's degree in Information Technology from HVL
- Bachelor's degree in Communication Systems from HVL
Other bachelor's degrees might qualify if you have at least 80 ECTS of Mathematics and Informatics/Computer Science. Out of these 80 ECTS, at least 40 ECTS must be in Informatics/Computer science, and at least 15 ECTS (at least two courses with 7,5 ECTS each) must be in Mathematics. If both INF100 and INF109 are part of the Bachelor's degree, the applicant will only get credits for INF100. One course in Statistics can count towards Mathematics (except STAT100). MNF130 (and equivalent) counts as Informatics.
For international self-financing applicants:
The Master's programme is not available for international applicants residing outside of the Nordic countries, the European Union/EEA and Switzerland.
You also need to document:
- Average grade of minimum C (equivalent to Norwegian grade C)
- Proficiency in English
Recommended previous knowledge
The following courses at University of Bergen, or their equivalents at other institutions:
MNF130 Discrete Structures
INF234 Algorithms
INF235 Complexity Theory
MAT121 Linear Algebra
MAT221 Discrete Mathematics
INF234 Algorithms and INF235 Complexity Theory can be taken either as part of the Master's programme or as part of the Bachelor's programme
Compulsory units
The master's programme consists of two components: Coursework of 60 credits and an individual research project (master's thesis) of 60 credits. It is possible to write a master's thesis of 30 credits.
Courses: The courses INF234 Algorithms, INF235 Complexity Theory and INF334 Advanced Algorithmic Techniques are compulsory.
Other courses must be on 200- or 300-level. In agreement with the supervisor, a maximum of 10 ECTS at 100-level can be chosen. Courses must be chosen in consultation with the supervisor to give a sufficient foundation for work with the master's thesis. INF399 Master's thesis in informatics consists of 60 ECTS (the student may choose a 30 ECTS after consultation with the supervisor, where the course section is expanded accordingly). The master's thesis must be submitted by a ficed deadline at the end of the fourth semester, either 20 November or 1 June.
If you aim for a broader relevant education for working life, we recommend completing a 30 ECTS master's thesis. You will thus have the opportunity to complete additional courses, a total of 90 ECTS, the first three semesters. The last semester you are working solely on your thesis.
If you envision continuing to a doctoral programme after completed master's studies or if you prefer spending more time on the thesis, a 60 ECTS thesis will suit you best. This will mean you complete three fewer courses than with a 30 ECTS thesis.
Recommended study plan for courses with a 30 ECTS thesis:
1. semester autumn: INF234, INF264 (Elective course), INF207 (Elective course)
2. semester spring: INF334, INF236 (Elective course), INF237 (Elective course)
3. semester autumn: INF235, INF270 (Elective course), INF258 (Elective course)
4. semester spring: Thesis
Recommended study plan for courses with a 60 ECTS thesis:
1. semester autumn: INF234, MAT 221 (Elective course), INF264 (Elective course)
2. semester spring: INF334, INF236/INF237 (Elective course), thesis
3. semester autumn: INF235, thesis
4. semester spring: Thesis
Recommended electives
INF339 - Selected topics in Algorithms and Complexity (irregular autumn / spring)
Autumn:
INF207 - Social Networks Theory
INF236 - Parallel programming
INF237 - Algorithms Engineering
INF252 - Visualization
INF358 - Seminar in visualization
INF264 - Introduction to Machine Learning
INF270 - Linear Programming
MAT221 - Discrete Mathematics
MAT227 - Combinatorics
Vår
INF227 - Introduction to Logic
INF250 - Foundations of data-orienterd visual computing
INF265 - Deep Learning
INF271 - Combinatorial Optimization (irregular)
Sequential Requirements, courses
The recommended sequence of the courses in the programme can be found under the heading "Compulsory units".
Study period abroad
You can plan study periods abroad in consultation with your supervisor as a part of the master agreement.
Teaching and learning methods
In preparing your master's thesis you will independently use methods and scientific working techniques from the subject field to research a relevant topic. In some cases, analyses of observation data and data from models are very important in addition to theoretical and experimental studies.
During the 1st semester the student establishes contact with a personal supervisor. Together with the supervisor a subject for the thesis is specified and a schedule is made with an outline of courses and milestones in the thesis work.
A combination of teaching methods is used in the various courses, mainly lectures and groups. You may find more information in the course description.
Assessment methods
The final step in the programme is an oral examination. The examination is held when the master's thesis is submitted, evaluated and approved.
The most common assessment methods in the courses are written and oral examination. The assessment methods for each course are described in the course description.
Grading scale
At UiB the grades are given in one of two possible grading scales: passed/failed and A to F.
The master's thesis will be graded A to F.
The grading scale for each course is given in the course description.
Diploma and Diploma supplement
The Diploma, in Norwegian, and the Diploma Supplement, in English, will be issued when the degree is completed.
Access to further studies
To be eligible for admission to the Doctoral education (PhD) the candidate must have completed a master's degree.
To qualify for the Doctoral education (PhD) at UiB the average grade for the master's thesis, the Master's degree and the bachelor's degree should be at least C.
In order to get enrolled you have to be granted a fellowship for doctoral training.
Employability
Information- and communication technology is more and more becoming a basic technology in all kinds of business activity and administration, and our candidates are strongly demanded to maintain and develop IT-systems. Many of the candidates also get employed by the IT-industry or within research and higher education.
Evaluation
The programme will be evaluated according to the quality assurance system of the University of Bergen.
Programme committee
The programme committee is responsible for the academic content, the structure and the quality of the programme.
Administrative responsibility
The Faculty of Mathematics and Natural Sciences by the Department of Informatics, holds the administrative responsibility for the programme.
Contact information
Please contact the academic adviser for the programme if you have any questions:
Studieveileder@ii.uib.no
Phone: + 47 55 58 42 00