The study program in information technology and economics aims to educate candidates with a broader educational background than the traditional economist or engineer, by combining topics in economics with subjects such as programming, data security, algorithms, and data science. The study will convey an understanding of how one can utilize the possibilities that the digitalization processes in society brings.

The program lies at the intersection between information technology and economics, and will link theory, empirical and practical skills, and will have great societal relevance. The candidates will be attractive in the labor market. They could for example handle digitization functions and lead the collection and analysis of market data in larger companies. They will also be driving forces for entrepreneurship and innovation processes through their interdisciplinary expertise.

At the beginning of the study, emphasis is placed on giving the students a solid knowledge in basic subjects within information technology, mathematics, statistics, and economics. The last half of the study is also interdisciplinary. In this part more options are given for specialization in ICT and economics. In the last part of the study program, the focus will be on developing the ability to solve economic and technical problems, both individually and in collaboration with others.

On completion of the program the candidate should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The candidate..

• has broad knowledge of theory and methods in information technology, for example in data security, data collection, machine learning, and artificial intelligence
• understands how economic theory explains price and interest rate formations, what efficiency in firms and in the economy entails, and how individuals and companies respond to changes in incentives
• can use economic principles to summarize and explain how information technology can be used to create value in the private and public sector
• has broad insight of the process of extracting knowledge from data using information technology for data collection and processing, and economics to form hypotheses and to interpret data
• has insight into practical problems related to the design and implementation of information technology systems, as well as analysis of data that these systems generate
• can apply knowledge to new areas within information technology and economics

Skills

The candidate..

• has solid knowledge in a wide range of methods based on economics and computer science and can use these for data management, analysis and problem solving
• can become acquainted with complex problems in information technology and find suitable solution methods, for example in data security, data acquisition, machine learning, and artificial intelligence
• can become familiar with complex economic issues, such as pricing of individual products, and is able to find suitable solution methods that involve the use of information technology, for example by designing systems for real-time processing of market data
• has the ability to integrate insights from economics and information technology to develop companies' value chains, for example through improved logistics and purchasing routines
• can use relevant literature in an active and critical way on new issues in the intersection between information technology and economics
• can use relevant methods for research and development, and in an independent way make quantitative calculations and empirical analyzes of economic and information technology issues and problems

General competence

The candidate..

• can communicate accurately and scientifically on current issues within information technology and economics
• can present complex issues in an easy-to-understand and accurate way to people in the private and public sector
• can contribute to problem solving in groups and collaborate across disciplines
• can apply their knowledge and skills in new areas to carry out advanced assignments and projects
• can work independently and organize and plan their own work within given deadlines
• has the ability to communicate information clearly, accurately, and as intended, with a high degree of logical and mathematical precision
• can contribute to innovation in the private and public sector through unique expertise in the intersection between information technology and finance

The study has two components: course part of 270 credits and individual master's thesis of 30 credits. All subjects that are not electives are compulsory. There is some flexibility in choosing courses.

• 1.semester (haust): ITØK101 (10 sp) - MAT111 (10 sp) - INFO132 (10 sp)
• 2.semester (vår): ITØK102 (10 sp) - INFO135 (10 sp) - MNF130 (10 sp)
• 3.semester (haust): INF170 (10 sp) - ECON210 (10 sp) - STAT110 (10 sp)
• 4.semester (vår): ITØK281 (10 sp) - ITØK264 (10 sp) - ECON263 (10 sp)
• 5.semester (haust): ITØK204 (10 sp) - INF140 (10 sp) - INFO180/INF161 (10 sp)
• 6.semester (vår): ITØK170 (10 sp) - INFO284 (10 sp) - https://www.uib.no/svf/109043/exphil-sv-studenterEX.PHIL. (10 sp)
• 7.semester (haust): ECON340 (10 sp) - ECON310 (10 sp) - Valemne INFO 200- eller 300-nivå/ INF 200-nivå (10 sp)
• 8.semester (vår): ITØK381 (10 sp) - ECON364/ ECON360/ ITØK320 (10 sp) - Valemne INFO 300- nivå/INF 200-nivå (10 sp)
• 9.semester (haust): Valemne ECON 300-nivå/ INFO 300-nivå/ INF 200-nivå /NHH (10 sp) - Valemne ECON 300-nivå / NHH (10 sp) - Valemne ECON 300-nivå / NHH (10 sp)
• 10.semester (vår): ITØK391 (30 sp)

List of particularly relevant elective courses. This list will change as new topics are added:

• INFO207 Sosial nettverksteori
• INFO215 Web Science
• INFO216 Knowledge graphs
• INFO319 Research topics in big data
• INFO323 Data Architectures for Information Retrieval and Web Intelligence
• INFO381 Research Topics in Artificial Intelligence
• INF234 Algoritmer
• INF270 Lineær programmering
• INF271 Kombinatorisk optimering
• INF273 Meta-Heuristikkar
• ECON316A Miljøøkonomi
• ECON316B Ressursøkonomi
• ECON327 Game theory
• ECON330 Makroøkonomisk analyse
• ECON341 Økonometri II
• ECON343 Empirisk forskningsdesign
• ECON362A Digital economics

1.semester

• ITØK101 Mikroøkonomi
• INFO132 Innføring i programmering
• MAT111 Grunnkurs i matematikk 1

2.semester

• ITØK102 Makroøkonomi
• INFO135 Vidarekommande programmering
• MNF130 Diskrete strukturar

3.semester

• INFO180 Metodar i kunstig intelligens/INF161 Innføring i data science
• ECON210 Velferd og økonomisk politikk
• STAT110 Grunnkurs i statistikk

4.semester

• ITØK281 Utplassering i informasjonsteknologi og økonomi
• INFO284 Machine learning
• ECON263 Bedriftsøkonomi for samfunnsøkonomar

5.semester

• ITØK204 Økonometri og dataanalyse
• INF140 Introduksjon til datatryggleik
• INF170 Modellering og optimering

6.semester

• ITØK170 Energi- og miljøfysikk
• ITØK264 Financial technology
• https://www.uib.no/svf/109043/exphil-sv-studenterExamen philosophicum

7.semester

• ECON340 Økonometri I
• ECON310 Mikroøkonomisk analyse
• Valemne INFO 200- eller 300-nivå/INF 200-nivå

8.semester

• ITØK381 Ekspertar i team
• ITØK320 Supply Chain Analytics/ ECON364 Corporate Finance/ECON360 Strategisk bedriftsadferd og markedsmakt
• Valemne INFO 300- nivå/INF 200-nivå

9.semester

• Valemne ECON 300-nivå or NHH
• Valemne ECON 300-nivå or NHH
• Valemne ECON 300-nivå /INFO 300-nivå/INF 200-nivå or NHH

10.semester

• ITØK391 (masteroppgave)

Different teaching methods are used to facilitate student activity and learning, for example problem-based learning and tasks/assignments that the students must solve in groups. The teaching also includes lectures and seminars in small groups - combined with feedback from the teacher and/or fellow students on written and oral work during the study.

The study also includes an internship, where students will contribute and solve problems for firms/organizations they are assigned to.

The master's thesis is a scientific work with guidance from assigned supervisors

The program provides specialist competence in information technology and economics, but also prepares candidates for later leadership positions through its interdisciplinary structure.

The need for knowledge on topics such as artificial intelligence and basic programming combined with solid knowledge in economics is great. The candidates will be able to utilize the knowledge and analyze issues in new areas within most industries, as well as in administration and research.