EPN-V2

Master's Programme in Applied Computer and Information Technology Programplan

Engelsk programnavn
Master's Programme in Applied Computer and Information Technology
Gjelder fra
2025 HØST
Studiepoeng
120 studiepoeng
Varighet
4 semestre
Programhistorikk

Innledning

Bachelorutdanningen for yrkesfaglærer i teknikk og industriell produksjon har et omfang på 180 studiepoeng (stp) og består av

  • profesjonsfag 60 stp med veiledet yrkespedagogisk praksis - pedagogikk 30 stp og yrkesdidaktikk 30 stp
  • yrkesfag 120 stp med veiledet yrkesfaglig praksis - yrkesfaglig bredde 60 stp

yrkesfaglig dybde 60 stp

 

Veiledet yrkespedagogisk og yrkesfaglig praksisopplæring inngår som en integrert del av de ulike fagområdene.

 

Bachelorutdanningen tilbys i tre ulike former:

Samlingsbasert

Opplæringen er samlingsbasert og nettstøttet, med samling på OsloMet på fredager. Studiet starter med en oppstartssamling på universitetet i begynnelsen av august. Mellom fellessamlingene er studentene inndelt i lokale tverrfaglige grupper som gjennomfører gruppemøter minimum én gang per uke.

 

Nettbasert

Opplæringen er nettbasert med en til to samlinger på campus i semesteret. Samlinger og veiledning skjer ellers via nett. Studentene organiseres i nettgrupper som gjennomfører ukentlige gruppemøter. Nettsamlingene i regi av faglærer foregår hovedsakelig på fredager, annen styrt studieaktivitet foregår etter avtale med studentgruppe og veileder. I tillegg er det lagt opp til annen nettaktivitet som kan gjennomføres fritt innenfor gitte tidsrammer. De samlingene som er på campus går som regel over to dager, henholdsvis fredag og lørdag. Studiet starter med en introduksjon på nett og en samling på OsloMet i august/september, som den første av to samlinger i det første semesteret.

 

Desentralisert

Opplæringen er samlingsbasert og noe nettstøttet, med samlinger i den aktuelle fylkeskommunen fredager og noen lørdager. Studiet starter med en oppstartssamling i august. Mellom fellessamlingene er studentene inndelt i lokale tverrfaglige grupper (basisgrupper) som gjennomfører gruppemøter minimum en gang per uke. I tillegg organiseres studentene i faggrupper (knyttet til yrkesfaget de tilhører). Det kan også være aktuelt med noe nettsamlinger og veiledning via nett.

Studiets innhold konsentreres om ledelse av læringsprosesser på ulike læringsarenaer med fokus på pedagogiske, yrkesdidaktiske, faglige og etiske kompetansekrav i det daglige arbeidet med elever/lærlinger. Opplæringen skal omfatte kjerneoppgaver som kartlegging, planlegging, tilrettelegging, gjennomføring, vurdering og dokumentasjon av læreprosesser som er tilpasset den enkelte elev/lærling og klasse/gruppe. I tillegg skal studiet gi kunnskap om skolens plass i samfunnet. Dette innebærer forståelse for skolens mandat, virksomhetens mål og egenart som organisasjon, arbeidsplass og læringsarena.

Studentene skal gjennomføre en tverrfaglig bacheloroppgave på 30 stp i 3. studieår

Profesjonsfaget

Profesjonsfaget består av yrkespedagogikk og yrkesdidaktikk og skal gi et nødvendig faglig grunnlag for profesjonell utøvelse av læreryrket. Med basis i profesjonsfaget, yrkesfag og praksis skal kandidaten gjøres i stand til å legge til rette for best mulig undervisning og læring for den enkelte elev i skolen. Det legges vekt på studentaktive læringsformer som fremmer egenrefleksjon, diskusjon og evne til kritisk begrunnelse av valg av innhold og metoder i opplæring. Gjennom yrkespedagogisk utviklingsarbeid er hensikten å styrke en forsknings- og utviklingsbasert tilnærming til utvikling av kunnskap og praksis.

 

Yrkespedagogikk

Studiet i yrkespedagogikk gir forståelse for hvordan ungdom og voksne videreutvikler kunnskaper, ferdigheter og generell kompetanse - og hvordan dette skjer i et samspill mellom individuelle og samfunnsmessige forhold. Arbeidet med pedagogisk teori skal belyse betingelser for, og prosesser som angår undervisning og læring i skole og arbeidsliv.

Pedagogisk teori skal også bidra med tolknings- og analyseredskaper for det praktiske lærerarbeidet og som referanseramme for studentenes praksiserfaringer. Pedagogikken skal gi grunnlag for refleksjon og valg i undervisningsplanlegging. Faginnholdet er rettet mot pedagogiske spørsmål relatert til yrkesutdanning og kunnskapsutvikling i skole og arbeidsliv.

Yrkesdidaktikk

Yrkesdidaktikk omfatter sentrale spørsmål som ligger i skjæringsfeltet mellom yrkeskvalifikasjoner og arbeidsoppgaver, faglig funderte kunnskaper, metoderedskaper, pedagogisk-psykologiske vurderinger og opplærings-, yrkes- og samfunnsrelaterte spørsmål. Problemstillingene omfatter både hva innholdet i et yrke er, hvorfor en arbeider med yrket, hvordan en arbeider med yrket i opplæringen og sammenhengen mellom disse perspektivene. Yrkesdidaktikk er innsiktet mot planlegging, gjennomføring og kritisk vurdering av undervisning og læring, der en tar utgangspunkt i yrkesoppgavene. Faginnholdet i yrkesdidaktikken, er rettet mot tilrettelegging, planlegging, gjennomføring, vurdering og kritisk analyse og utvikling av yrkesrelaterte arbeidsprosesser i skole og bedrift.

Yrkesfaget

Yrkesfaget skal videreutvikle studentenes yrkesfaglig kompetanse utover Vg3-nivå innenfor sitt yrkesfag (yrkesfaglig dybde), og gi innsikt i fellestrekk og særtrekk i de fagene/yrkene som inngår i utdanningsprogrammet studentene skal undervise i (yrkesfaglig bredde). Yrkesfaget knyttes til profesjonsfaget og yrkesfaglig praksis i arbeidslivet, og skal være gjennomgående i hele studieløpet.

Yrkesfaglig bredde

Studiet i yrkesfaglig bredde for teknikk og industriell produksjon skal gi kunnskaper om planlegging, tilrettelegging, gjennomføring og kritisk vurdering av opplæring yrkene i studieprogrammet. Det er lagt vekt på samsvar mellom studentenes opplæring og fagopplæringen slik den kommer til uttrykk i bransjen. Studentene skal tilegne seg yrkeskunnskaper som er nødvendige for å kunne undervise i grunnopplæringen i fagområdet. Målene skal framstå i en helhetlig sammenheng og være styrende i forhold til praktiske læringsoppgaver.

Innholdskomponenten for yrkesfaglig bredde tar utgangspunkt i kompetansebeskrivelsene for Vg1 Teknikk og industriell produksjon:

  • grunnleggende ferdigheter
  • entreprenørskap
  • produksjon
  • tekniske tjenester
  • dokumentasjon og kvalitet
  • yrkesfaglig fordypning

 

Yrkesfaglig dybde

Studiet i yrkesfaglig dybde for teknikk og industriell produksjon skal utvikle og forsterke studentens egen yrkeskompetanse. Studentens praktiske erfaringsbakgrunn fra eget yrke og fagbrevområde skal være styrende i forhold til oppbygging og vektlegging av opplæringen. Fordypning innen eget yrkesområde er beskrevet som læringsutbytte for hvert emne i fagplanen. Grad av fordypning i de ulike målområdene vektlegges ut fra behov for utøvelsen av yrket som yrkesfaglærer. I yrkesfaglig dybde skal studentene utvikle sin forståelse for yrkesfaglige prosesser innen eget yrkesområde.

Innholdskomponenten tar utgangspunkt i kompetansebeskrivelsene for Vg2 og Vg3 innen de forskjellige programfagene. Den enkelte students kompetanse skal videreutvikles utover Vg3-nivå innenfor eget yrkesfag.

1. Arbeidsmaskiner

  • feilsøking og reparasjon
  • dokumentasjon og kvalitet
  • faglig fordypningsprosjekt

Anleggsmaskinmekanikerfaget og landbruksmaskinmekanikerfaget er fordypningsyrker som ligger under dette området.

2. Bilskade, Lakk og karosseri

  • karosseri- og lakkteknikk
  • dokumentasjon og vedlikehold
  • faglig fordypningsprosjekt

Billakkererfaget, bilskadefaget og chassispåbyggerfaget er fordypningsyrker som ligger under dette området.

3. Brønnteknikk

  • leiting, boring og komplettering
  • produksjon og brønnvedlikehold
  • HMS og kvalitet
  • faglig fordypningsprosjekt

Boreoperatørfaget, brønnfaget elektriske kabeloperasjoner, brønnfaget havbunnsinstallasjoner, brønnfaget komplettering, brønnfaget kveilerøroperasjoner, brønnfaget mekaniske kabeloperasjoner, brønnfaget sementering er fordypningsyrker som ligger under dette området.

4. Industriell møbelproduksjon

  • produktutvikling og produksjon
  • materiale og teknikker
  • dokumentasjon og kvalitet
  • faglig fordypningsprosjekt

Industrisnekkerfaget og industritapetsererfaget er fordypningsyrker som ligger under dette området.

5. Industriteknologi

  • produksjon
  • reparasjon og vedlikehold
  • dokumentasjon og kvalitet
  • faglig fordypningsprosjekt

Aluminiumskonstruksjonsfaget, bokbinderfaget, CNC-operatørfaget, dimensjonskontrollfaget, finmekanikerfaget, grafisk emballasjefaget, industrimekanikerfaget, industrimontørfaget, industriell overflatebehandling, industrioppmålingsfaget, industrirørleggerfaget, kran- og løfteoperasjonsfaget, modellbyggerfaget, NDT-kontrollørfaget, produksjonsteknikkfaget, plastmekanikerfaget, platearbeiderfaget, polymerkomposittfaget, termoplastfaget, trykkerfaget, serigrafifaget, støperifaget, sveisefaget og verktøymakerfaget er fordypningsyrker som ligger under dette området.

6. Industritekstil og design

  • produksjonsforberedelse
  • materialer og materialbruk
  • produksjon og styring

Industrisømfaget, industritekstilfaget/farging/trykking og etterbehandling, industritekstilfaget-fiskeredskap, industritekstilfaget-garnframstilling, industritekstilfaget-trikotasje, industritekstilfaget-veving er fordypningsyrker som ligger under dette området.

7. Kjemiprosess

  • produksjon og vedlikehold
  • kjemisk teknologi
  • dokumentasjon og kvalitet
  • faglig fordypningsprosjekt

Kjemiprosessfaget er fordypningsyrke som ligger under dette området

8. Kjøretøy

  • verkstedarbeid
  • dokumentasjon og kvalitet
  • faglig fordypningsprosjekt

Bilfaget, lette kjøretøy, bilfaget, tunge kjøretøy, hjulutrustningsfaget, motormekanikerfaget, motorsykkelfaget og reservedelsfaget er fordypningsyrker som ligger under dette området.

9. Laboratoriefag

  • laboratoriearbeid
  • dokumentasjon og kvalitet
  • faglig fordypningsprosjekt

Laboratoriefaget er fordypningsyrke som ligger under dette området

10. Maritime fag

  • drift og operasjon
  • skipstekniske tjenester
  • dokumentasjon og kvalitet
  • faglig fordypningsprosjekt

Matrosfaget og motormannfaget er fordypningsyrker som ligger under dette området.

11. Særløpsfag

  • produksjon og utvikling
  • faglig fordypningsprosjekt

Garverifaget, gjenvinningsfaget, industriell skotøyproduksjon, låsesmedfaget, tekstilrensfaget og vaskerifaget er fordypningsyrker som ligger under dette området.

 

Fritak/godskriving av tidligere utdanning

Forskrift om rammeplan for yrkesfaglærerutdanningen 8-13 trinn § 5 og Universitets- og høgskoleloven § 3-5 regulerer fritak/godskriving av tidligere utdanning.

I tillegg kan det gis fritak fra deler av studiet på grunnlag av realkompetanse, dvs kompetanse som er oppnådd på andre måter enn gjennom formell universitets- eller høgskoleutdanning, jfr. Retningslinjer for fritak for deler av studium ved OsloMet - storbyuniversitetet på grunnlag av realkompetanse.

Vurderingen av om det gis fritak/godskriving gjøres på bakgrunn av søknad med aktuelle vedlegg fra studenten, og det er klagerett på vedtaket.

Målgruppe

Studiet krever at studentene er aktive deltakere på samlinger og at de bidrar med sine refleksjoner og erfaringer i det læringsfellesskapet klassen utgjør. Innhold og arbeidsmåter i studiet krever tilstedeværelse og deltakelse, derfor er det obligatorisk å være med på samlingene. Studiet tilbys også nettbasert.

Arbeids- og undervisningsform vil gjennom studie ha en bred variasjon slik som;

Entreprenørskap, praksisorientering, problemorientering, eksemplarisk læring, erfaringslæring, opplevelsesorientering, verdiorientering, målstyring, studentinnflytelse, ekskursjoner, kasusbeskrivelser, instruksjons- og undervisningsøvelser, forelesninger, gruppearbeider, basis-/kollokviegrupper, selvstudier, prosjekt- og temaarbeid, rollespill, studentframlegg, loggskriving og veiledning underveis, samt vurdering og tilbakemelding etter gjennomførte oppgaver.

Faglærer og studenter velger og begrunner de forskjellige arbeidsformer i hvert enkelt emne ut fra pedagogisk- og/eller yrkesfaglig forankring.

Følgende yrkespedagogiske prinsipper ligger til grunn for valg av arbeidsformer og organisering av innhold:

  • Praksisorientering

Utgangspunktet for studiet er utfordringer og oppgaver i læreryrket. Dette betyr at studentenes erfaringer fra praksisfeltet og refleksjoner knyttet til dette har en sentral plass i studiet.

  • Problemorientering

Studentene skal lære gjennom å arbeide med virkelighetsnære problemstillinger og situasjoner. Problemorienteringen kan gjennomføres ved for eksempel observasjons-/feltstudier, problembasert læring og oppgaveløsning, prosjektarbeid og utviklingsarbeid.

  • Opplevelsesorientering

Studentene skal bli bevisst og kunne gi uttrykk for sine følelser og tanker i ulike situasjoner. De skal også kunne tilrettelegge for slike læringsprosesser hos sine elever.

  • Erfaringslæring

Det vil si å gjøre seg bevisst tidligere erfaringer og gjøre seg nye erfaringer med ulike former for pedagogisk arbeid. Gjennom å planlegge, prøve ut og reflektere over ny praksis vil studentene øke bevissthet og handlingsregister i ulike opplæringssituasjoner.

  • Eksemplarisk læring

Studentene lærer ved at egnede eksempler analyseres, bearbeides, anvendes og generaliseres for bruk i egen praksis.

  • Verdiorientering

Studentene skal bli bevisst og klargjøre sine normer og holdninger i forhold til yrkesetiske standarder og konsekvenser av egne valg.

  • Studentinnflytelse og målstyring

Studentene skal utarbeide mål og planer for egen læring. De skal delta i planlegging av studieforløpet innenfor rammene i programplanen og trekkes med i en fortløpende vurdering av studieopplegg, undervisnings- og læringsprosesser.

Studiet er planlagt med stigende krav til selvstendighet og ansvar for egne læreprosesser.

Opptakskrav

Praksisopplæringen skal bidra til at studentene oppnår relevant og god kompetanse for sin framtidige utøvelse av læreryrket. I praksisopplæringen skal studentene prøve ut og bearbeide egne relevante erfaringer og refleksjoner i forhold til læringsutbyttene i studiet. Praksisen deles i yrkesfaglig praksis og pedagogisk praksis:

  • Yrkesfaglig praksis skal være på minimum 60 dager, med veiledning fra instruktør/faglig leder og/eller faglærer. Målet med denne praksisen er at studenten får innsikt i det daglige arbeidet og yrkesprosesser på arbeidsplassen.
  • Pedagogisk praksis skal tilsvare totalt 70 dager med veiledning knyttet til profesjonsfaget. Praksisopplæringen består av de aktiviteter som inngår i en lærers arbeidsplanfestede dag.

 

Yrkesfaglig praksis

Hensikten med yrkesfaglig praksis er at studentene får innsikt i de ulike yrkene som inngår i utdanningsprogrammet (breddekunnskap) og fordypning i eget yrke (dybdekunnskap).

Alle yrkesfaglige praksisperioder skal dokumenteres, godkjennes og kommenteres av faglærer.

 

Pedagogisk praksis

Alle studenter skal gjennomføre pedagogisk praksis på ungdomstrinnet, minimum 10 dager, og i videregående opplæring i eget programområde på ulike trinn i 60 dager. Totalt skal studentene gjennomføre 70 hele dager i pedagogisk praksis.

Den pedagogiske praksisen skal være veiledet, variert og vurdert. De 4 ulike periodene er knyttet til 4 ulike emner og vurderes til bestått/ikke bestått etter hver periode. Praksisen skal ha gradvis progresjon fra observasjonspraksis til individuell undervisningspraksis. Det vil derfor bli stilt strengere krav for å bestå en praksisperiode på slutten av studiet enn i begynnelsen av studiet. Den enkelte praksisperiode må bestås før neste periode kan påbegynnes.

Det er utarbeidet en egen praksisguide for pedagogisk praksis i yrkesfaglærerutdanningen https://student.hioa.no/praksis-ylu

Hvis en student ikke består en praksisperiode kan denne gjennomføres på nytt. Får studenten vurdert samme praksisperiode til ikke bestått to ganger må studiet avbrytes, jf. § 8-4 i forskrift om studier og eksamen ved Høgskolen i Oslo og Akershus

Læringsutbytte

On successful completion of their Master's degree, the candidate should have the following qualifications defined in knowledge, skills and general competence:

Knowledge

Upon successful completion of the program, the candidate:

  1. has thorough knowledge of the professions within applied computer and information technology and their role in businesses, organisations and society
  2. has a thorough knowledge of the processes and methodologies applied by professional practitioners within fields like information technology, scientific computing and electrical engineering or a combination of these traditional fields, both in public and private sector
  3. has an advanced understanding of how technological advances in society are alloys of multiple disciplines, such as Mathematics, Computer Science, Electrical Engineering and more
  4. has a fundamental understanding of a secondary field within applied computer and information technology and its role in organisations and society
  5. has thorough experience in interdisciplinary work and how it contributes to solving complex problems

Skills

Upon successful completion of the program, the candidate:

  1. can contribute to innovation processes in applied computer and information technology by harnessing knowledge and skills from a research discipline, such as Computer Science, Electrical Engineering or Mathematics, and directing them towards an interdisciplinary problem
  2. can facilitate, nourish and cultivate interdisciplinary perspectives in projects
  3. can design and implement technical solutions to challenges that represent modern and real-life scenarios
  4. can translate abstract theoretical models or technical descriptions into working solutions and systems, relative to their area of focus
  5. can analyze existing theories, methods and interpretations in their field and work independently on practical and theoretical problems
  6. can use relevant methods for research, scholarly and development work within their field in an independent manner
  7. can carry out independent research or development project within their field under supervision and in accordance with applicable norms for research ethics
  8. can identify and communicate common facets and challenges within their field to professionals from other fields
  9. can deploy, use and manage systems and technical tools that in complexity and scale represent enterprise scenarios
  10. can independently update their knowledge as technology progresses to new areas within society
  11. can apply knowledge to new areas within their academic field
  12. can analyze academic problems within their area of research based on its methods, tradition and role in society

General Competence

Upon successful completion of the program, the candidate:

  1. can appreciate why evaluating a technological challenge beyond the perspective of a single discipline is needed in the pursuit of a safe, inclusive and responsible technologically advanced society
  2. can analyze relevant academic, professional and research ethical problems in applied computer and information technology
  3. can apply his/her knowledge and skills in new areas in order to carry out advanced assignments in the realm of technology
  4. can communicate extensive independent work and masters language and terminology of their own academic field or an interdisciplinary field
  5. can communicate about academic and professional issues, analyses and conclusions in their field, both with specialists and the general public
  6. can contribute to new thinking and innovation processes

Innhold og oppbygging

ACIT is a combination of courses and a thesis project at the end. Students can choose between a short or a long thesis project. The program is designed to first focus on a specialisation before introducing training as a specialist in interdisciplinary work. Every specialisation has three core courses, called specialisation courses (SPEC). When following a specialisation, the corresponding SPEC courses become mandatory courses.

In addition, there are two courses common for all specialisations. These two courses focus on research methods and ethics and interdisciplinary innovation. Finally, every student will take an alternative specialisation course (ASPEC), which is one of the two first specialisation course that belongs to a different specialisation than their own. The student is free to choose what ASPEC course to take based on their individual interest, applicability for their research project or for a specific career profile, as along any prerequisite knowledge requirements are met.

Requiring students to take a specialisation topic outside their own specialisation, gives them a broader scholarly perspective and provides a platform for interacting with students, teachers and researchers from other fields, increasing students' interdisciplinary knowledge and skillsets.

In summary, the core structure for all students is:

30 ECTS Specialisation courses (SPEC)

20 ECTS Common courses

10 ECTS Alternative specialisation course (ASPEC)

60 ECTS Long Thesis or 30 ECTS Elective courses and 30 ECTS Short Thesis

The table below illustrates the program structure for a student selecting a long thesis. The two common courses are placed in the first and second semester. The specialisation courses are also within that timeframe but the master thesis project is divided into three phases where the first phase is in the second semester. This structure allows for the project to mature over three semesters instead of two. It also enables the student to pick an alternative specialisation course that would supplement the thesis project after familiarizing more thoroughly with the project and its scope.

Sem 1: 10 ECTS Common course + 2 x 10 ECTS Specialisation course

Sem 2: 10 ECTS Common course + 10 ECTS Specialisation course + 10 ECTS Master's Thesis Phase 1

Sem 3: 10 ECTS Alternative specialisation course + 20 ECTS Master's Thesis Phase 2

Sem 4: 30 ECTS Master's Thesis Phase 3

The structure for a short thesis is shown in the next table. The placement of the common and specialisation courses is the same as before, but there is more space in the second and third semester to take additional elective courses. The thesis project takes place in the final semester.

Sem 1: 10 ECTS Common course + 2 x 10 ECTS Specialisation course

Sem 2: 10 ECTS Common course + 10 ECTS Specialisation course + 10 ECTS Elective

Sem 3: 10 ECTS Alternative specialisation course + 2 x 10 ECTS Elective

Sem 4: 30 ECTS Master's Thesis

Common course content

ACIT has two common courses which are mandatory for all students in the program. The first common course, Understanding and Communcating Research introduces the student to scientific writing, finding and understanding research papers and the ethical standards that follow a researcher and professional. The ability to communicate effectively is an important asset of any researcher, as research is not done in a vacuum. We need to communicate our challenges and findings to others, be that fellow researchers, politicians or in the general public domain. In each case, the format has to be adapted to the audience, so todays researcher must master a wider range of communication than before. Finding, reading and understanding scientific literature can be a cumbersome process. Our students will learn techniques to find, sort and organize the literature they seek in order to get the most out of it.

Each scientist relies on a set of methodologies, that define the rules and methods for their design, development, data gathering and analysis. These methods can vary based on the particular field of the researcher and ideally every researcher should know every method from every field. Instead, however, one must focus on the most common methods used in their domain. This course offers a broad perspective on the range of methods available but will offer more specialized topics to each student based on their field.

The second common course, Interdisciplinary Innovation: using diversity to solve complex problems, is an important course for the student to get training in how to be an expert among other experts from other fields. In this course, students will work together in diverse groups to address or solve a challenge given to them from our own researchers or outside partners. Students will be trained in design and innovation processes, focusing on the ability to interact with team members building on each others' respective knowledge and skills.

Specialisation track content

Each specialisation track offers in-depth knowledge into a field that has both academic and industrial applications. Below are descriptions of the content one will find in each track.

Together with the description, we list the specialisation courses for the track and also provide a list of Recommended Prior Knowledge. This list is not a formal requirement for admission to the program, but should help the student understand what to expect and also enable them to study up on the topics beforehand in order to avoid steep learning curves. They can also use this information to select courses that further enhance their knowledge in those areas.

Representatives from the program committee can provide a list of literature and digital resources that can be used for self-study.

Applied Artificial Intelligence

Specialisation courses (SPEC)

ACIT4610 - Evolutionary artificial intelligence and robotics (1st Semester)

ACIT4620 - Computational Intelligence (1st Semester)

ACIT4630 - Advanced machine learning and deep learning (2nd Semester)

This specialisation focuses on the understanding, the development, and the application of artificial intelligence methods and tools to solve a variety of real world problems. Artificial intelligence will revolutionize the way people live and work. This specialisation gives you the advantage to work with cutting edge technologies and acquire the skill required in the present and in the future. During your studies, you will learn state-of-the-art algorithms and tools within artificial intelligence, such as deep learning, reinforcement learning, as well as evolutionary and biologically inspired algorithms, swarm intelligence, and other methods used in research and in the industry. You will not only learn the methods and theory, but you will also focus on practical projects that will give you the necessary experience and expertise to apply the methods to solve problems in different domains.

The specialisation track objectives for Applied Artificial Intelligence are:

The students will learn the foundation and inspiration of modern artificial intelligence methods and tools

The students will gain practical experience and technical skills in applying artificial intelligence to solve problems in different areas

The students will be able to understand the challenges and implications of applied artificial intelligence, and the impact AI can have on society, work, and daily life.

ACIT4620 - Computational Intelligence will provide prerequisite/foundational materials to support other two more advanced courses on "deep learning" and "evolutionary AI". In this way, the students will have a complete, holistic and coherent understanding of the AI field.

The course in "ACIT4610 - Evolutionary artificial intelligence and robotics" will provide the basis for modelling and analyzing complex systems, programming and controlling them with biologically inspired artificial intelligence, swarm intelligence, and evolutionary robotics. This course will provide insight into creating autonomous machines and systems that can adapt, evolve, and learn over time.

In the second semester, the course "ACIT4630 - Advanced machine learning and deep learning" focuses on how to use advanced AI algorithms that allow computers and machines to learn through deep learning and reinforcement learning. Such state-of-the-art techniques are currently used to perform difficult cognitive tasks at a level that is often superior to humans, such as pattern recognition and diagnosis in medical images, self-driving cars, or natural language understanding. During this course, the students will apply machine learning to solve problems in domains of their interest.

This specialisation can be supplemented with the "ACIT4040 - Applied artificial intelligence project" where students in teams will develop a complete artificial intelligence system from scratch, or with the course on "ACIT4030 - Machine Learning for 3D Computer Vision" which will focus on AI applications in the domain of graphics and computer vision. Several other specialisation courses from other tracks can complete the program with relevant skills within data science, mathematics or robotics.

Recommended, but not required, prior knowledge

Programming (e.g. Python)

Bachelor level knowledge of linear algebra

Bachelor level knowledge of vector calculus

Basic statistics and probability

Electronics and Biomedical Systems

Specialisation courses (SPEC)

ACIT4720 - Medical sensors and actuators (1st semester)

ACIT4740 - Microelectronic Circuits and systems (1st semester)

ACIT4730 - Special biomedical engineering subject (2nd semester)

Electronics and Biomedical Systems studies ways to improve the diagnostics, therapy, care, rehabilitation and life quality by researching and developing diagnostic and therapeutic devices, equipment, implants, medical imaging systems as well as pharmaceuticals. This specialisation in particular involves the hardware and software design of devices and systems used to measure biological signals and activities. This ranges from developing sensors that can capture a biological signal of interest, to applying methods of amplifying and filtering the signal so that it can be further studied, to dealing with sources of interference that can corrupt a signal, to building a complete instrumentation system such as an x-ray machine or a heart monitoring system.

The specialisation track objectives for Electronics and Biomedical Systems are:

The student will acquire advanced knowledge in hardware and software design and learn how to analyse different problems related to biology and medicine and implement those solutions in a cross disciplinary field.

The student will gain skills in evaluating existing instrumentations and systems that are applied in the laboratories and clinics, and develop specific solutions that are ideally innovative and practically anchored.

The student will understand how different hardware and software approaches are applied in a field where the challenges are created by the diversity and complexity of living systems, which require creative, knowledgeable, and imaginative solutions.

In this specialisation, the first two courses focus on the fundamentals of microelectronic systems, sensors, and measurement's techniques. The course "ACIT4720 - Medical sensors and actuators" focuses basics of measurements techniques with examples of different sensory schemes that are applied in biomedical applications. ACIT4740 - Microelectronic Circuits and Systems covers the fundamentals of microelectronic systems with emphasis on contemporary building blocks and architectures.

The course "ACIT4730 - Special biomedical engineering subject" focuses on specific technology and methods that the candidate may be involved specifically through the master project.

Suggestion for these themes can be varied from special applications within diagnostic and prognosis. Other suggested themes can be embedded systems, multivariate analysis techniques, design of optical fibres, mechatronics systems, and design of lab on chip or CD with focus on biomarkers.

In addition, the following elective courses are suggested: "ACIT4015 - Internet of Things", "ACIT4030 - Machine Learning for 3D Computer Vision", “ACIT4040 - Applied AI project”, "ACIT4080 - Intelligent User Interfaces" and "ACIT4035 - Rehabilitation and assistive devices".

This specialisation can be supplemented with many other specialisation courses from other tracks such as Robotics, ACIT4630 - Advanced Machine Learning and Deep Learning, ACIT4530 - Data Mining at Scale: Algorithms and Systems and ACIT4320 - Quantum Information Technology. Students who wish to improve their programming skills could benefit from taking the course "ACIT4420 - Problem-solving with scripting". In addition, subjects "Biomechanics", and "Cellular physiology" from faculty of health sciences could be complementary in this specialisation.

Recommended, but not required, prior knowledge:

Anatomy and physiology

Electronics

Biomedical equipement

Electrical safety

Basic programming

Cloud-based Services and Operations

Specialisation courses (SPEC)

ACIT4410 - Agile Service Delivery and Developer Operations (1st Semester)

ACIT4420 - Problem solving with scripting (1st Semester)

ACIT4430 - Infrastructure Services and Operations (2nd Semester)

Today, the cloud is an essential platform for services that need to display automated and agile features. Software engineering is not enough, as that focuses much on the process of designing and developing software. What is needed in addition is a thorough technical foundation as well where the entire platform stack is covered.

This specialisation focuses on the process of developing, deploying and managing large-scale services. This combines an understanding of how modern development teams work, how parts of the development process can be automated in order to achieve higher efficiency and finally how a service can be supported by an operations infrastructure in order to make it robust and flexible enough to scale to a world audience. A practical focus will be found in all three specialisation courses, aiming to deliver technical competence as well as an birds-eye view of how the IT industry and academia meets the demand of a digitized society.

The specialisation track objectives for Cloud-based Services and Operations are:

The student will learn the role large-scale cloud-based services play in a digitized society

The student will gain technical skills and unique knowledge to become a valuable member of software engineering or operations teams

The student will understand the current challenges of cloud-based operations and can discuss them

In this specialisation, the first two courses focus on how to package and deploy services in cloud-based environments as well as how to develop scripts for automating that process. This builds naturally on general IT programming, web-development and software engineering topics commonly found in bachelor programs. The course "ACIT4410 - Agile Service Delivery and Developer Operations" is a unique introduction into the most modern ways services are deployed and managed, covering topics such as containers, IaaS, PaaS, scaling and Site Reliability Engineering (SRE). In the course "ACIT4420 - Problem solving with scripting" the students can put their new knowledge into projects that allow them to build sophisticated frameworks for automated service management.

In the second semester, the course "ACIT4430 - Infrastructure Services and Operations" focuses on how to build a wider scaffolding of robustness around a service by providing features such as monitoring, configuration management, centralized logging and backup. This course aims to enhance the knowledge from the previous semester with a deeper understanding on how to make a service function well over its entire lifecycle as well as provide a better understanding of how operations teams work to achieve it.

This specialisation can be supplemented with more core infrastructure courses, such as Enterprise networking and security. Many other specialisation courses from other tracks will also work favorably with these topics as internet-based services and agile software delivery are a relevant element of most of the IT industry.

Recommended, but not required, prior knowledge

Basic operating systems concepts

Networking

Web Programming

Basic Linux/Mac OS command-line

Version Control Systems, like Git

Cyber Security

Specialisation courses (SPEC)

ACIT4050 – Applied Computer and Network Security (1st semester)

ACIT4280 – Privacy by Design (1st semester)

ACIT4290 – Practical Cyber Security (2nd semester)

Elective courses

ACIT4025 - Cyber Security and Privacy (Autumn semester)

ACIT4055 - Security politics, cyberwar and ethics (Spring semester)

The purpose of cyber security studies is to provide individuals with the knowledge and skills to help protect computer systems, networks, and other digital devices from unauthorized access, attacks, and theft. It also aims to promote safe and responsible use of technology, raise awareness about cyber threats and risks, and encourage proactive measures to prevent cyber incidents. Cyber security education helps individuals to understand the magnitude of cyber threats and their potential impact on personal and professional lives. It prepares them to identify, analyze, and mitigate cyber risks and vulnerabilities, and equips them with techniques to respond to cyber-attacks appropriately. Additionally, cyber security education supports the development of a skilled workforce in the field of cyber security to meet the growing demand for cyber security professionals.

The specialisation objectives for Cyber Security are:

The student will acquire advanced knowledge of defensive and offensive cyber security and learn how to analyze threats and vulnerabilities as well as to plan solutions and mitigations to those threats.

The student will gain deep insights into information privacy and data protection and will learn risk and impact assessments methods as well as strategies and tools for designing data protection into data systems.

The student will acquire professional ethics by studying the impact and consequences of cyber security, the lack thereof, and the consequences of mishandling personal information. Societal impact, ethical perspectives and cyber politics will second technical expert knowledge.

Recommended, but not required, prior knowledge for successful studies in cyber security:

General knowledge about information security from OsloMet’s course ITPE3100 Datasikkerhet (or equivalent courses with compatible curriculum).

Bachelor project with relationship to information security/information privacy

Introductory knowledge in cryptography and its applications (encryption, digital cash, blockchain, digital signatures, digital identities, and other topics)

Bachelor-level knowledge in programming, software engineering, networking

Ability to read and process literature in English.

Data Science

Specialisation courses (SPEC)

ACIT4510 - Statistical Learning (1st Semester)

ACIT4620 - Computational Intelligence (1st Semester)

ACIT4530 - Data Mining at Scale (2nd Semester)

In Data Science you will find elements of Big Data, Statistics and Machine Learning. With the vast amount of data available to us from all forms of electronic devices and systems, the challenge remains to extract knowledge and wisdom from it. Examples of current challenges where data analysis is needed are: self-driving vehicles that share information and learn from each other, climate data from across the globe, financial transactions from millions of bank customers or genomic datasets from gene banks. As technology continues to spread into every nook of our lives, new data about us is generated. Even though valuable insight can be found, the need to protect the data and understand the ethical ramifications of its use becomes ever more important.

Being a Data Scientist means having practical skills in order to set up and use advanced Big Data databases, next it requires competence in statistics in order to know what methods of analysis are most applicable. Finally, it requires the ability to automate the analysis to be turned into a tool that can be used by others on future, similar datasets.

The specialisation track objectives for the Data Science track are:

The student will learn to utilize statistical methods on large data sets in practice

The student will get practical experience on state-of-the-art BigData systems

The student will get theoretical background in the algorithms and techniques used in Data Science

The student will program their own analysis tools based on the methods they have learned to be used on large data sets

The two specialisation courses for this track, "ACIT4510 - Statistical Learning" and "ACIT4530 - Data Mining at Scale", provide a foundation of multiple methods of structuring and analyzing datasets. This involves topics ranging from statistics, machine learning and pattern mining as well as becoming familiar with platforms that can be used to store, organize and run computations on the data. The specialisation course "ACIT4620 - Computational Intelligence", will be shared with the Applied Articifial Intelligence specialisation and allow students to integrate AI concepts.

“ACIT4011 - Graph Data Management” can be a relevant supplement to the Data Science specialisation. Students from this track will find interesting connections to all the other specialisation tracks. Courses from Applied Artificial Intelligence and Mathematical Modelling and Quantum Technologies will let the student go deeper on the learning and analysis aspects. Courses from Cloud-based Services and Operations will be interesting for students who want to focus more on the technical aspects and management of BigData architectures. Other specialisation tracks will offer relevant use cases for Data Science, such as health data from Biomedical Engineering, sensor data from Robotics and Control.

Recommended, but not required, prior knowledge

Database systems

Basic statistics like probability theory and common tests

Basic programming

Linear algebra

Algorithms and data structures

Mathematical Modelling and Quantum Technologies

Specialisation courses (SPEC)

ACIT4310 - Applied and Computational Mathematics (1st Semester)

ACIT4321 - Quantum Information Technology (1st Semester)

ACIT4330 - Mathematical Analysis (2nd Semester)

Mathematical models are widespread in science and engineering and, as we spend much of our time on the internet, even surround us in everyday life. Whenever we want to create a representation of the real world that allows us to investigate and simulate it, we reach for mathematics as a language. Today, mathematicians work alongside engineers and scientists to address major challenges in our world, such as understanding and predicting the effect of climate change or describing both atomic building blocks and the vast limits of the universe. Mathematicians work in the computer game industry to provide models of how physics affects artifacts or how economies within games can be balanced. The most powerful supercomputers in the world are designed for that purpose only: run vast mathematical computations. Common for these examples is that the expert both has a solid mathematical skillset to utilize on their context but also the ability to translate the relevant models into technical solutions. Programming mathematical models into executable tools for analysts is a central ingredient in this specialisation.

The mathematical modelling and quantum technologies specialisation prepares students for developing and treating models in their own projects and for jobs in research, industry and IT where mathematical modelling and simulation is essential. The typical student will know her way around theoretical mathematics and use this theory to implement mathematical and computational methods on a computer, run numerical simulations and interpret simulation results in terms of the problem at hand. Thus, students in this specialisation should become proficient in all parts of the modelling process.

Students in the Mathematical Modelling and Quantum Technologies track will:

build a substantial portfolio of analytical techniques and computational methods and be able to implement these methods for scientific computing

gain insight into how mathematical models are built and be aware of strengths and limitations of mathematical modelling

learn how to apply theory and interpret model results in the context of science and engineering

The introductory course in the Mathematical Modelling and Quantum Technologies specialisation ("ACIT4310 - Applied and Computational Mathematics") focuses on the model concept, why we need models, and how we apply various mathematical and computational methods to analyze and simulate models. The course "ACIT4321 - Quantum Information Technology" will introduce students to key concepts within classical information theory the fundamentals of quantum phenomena, and be trained to create their own quantum algorithms, simulate quantum systems, and implement the corresponding programs on classical and quantum computers. Prior knowledge in quantum physics is not required. In the second semester, the course "ACIT4330 - Mathematical Analysis" provides a deeper understanding of mathematical concepts and gives the theoretical background of many of the results used in the first courses.

There is a range of relevant specialisation courses from other tracks that can be suitable for Mathematical Modelling and Quantum Technologies students. Mathematically oriented courses include "ACIT4610 - Evolutionary AI and robotics" and "ACIT4530 - Data Mining at Scale: Algorithms and Systems" from the artificial intelligence and data science tracks. The course "ACIT4410 - Agile Service Delivery and Developer Operations" is a useful supplement if packaging the analysis into tools and products is of interest. Students who wish to improve their programming skills could benefit from taking the course "ACIT4420 - Problem-solving with scripting" (several tracks).

Recommended, but not required, prior knowledge

Basics of numerical methods

Basic mathematical analysis

Basic physics

Basic programming

Robotics and Control

Specialisation courses (SPEC)

ACIT4810 - Advanced Methods in Modelling, Simulation, and Control (1st Semester)

ACIT4820 - Applied Robotics and Autonomous Systems (1st Semester)

ACIT4830 - Special Robotics and Control Subject (2nd Semester)

The specialisation in Robotics and Control focuses on understanding the technologies and methodologies behind modern robots, drones, advanced industrial process control and autonomous systems in general. Robotics is becoming increasingly important for home, industrial, transport and medical applications. The deployment of autonomous self-guiding vehicles, including autonomous ships and drones, is expected to grow massively in the coming years with the need for highly skilled professionals. The specialisation combines traditional robotics and control systems with novel computing technologies, such as artificial intelligence and machine learning. These skills are extremely relevant for current and future companies working on product development, smart manufacturing technologies, and Industry 4.0.

During the study, you will obtain knowledge in key topics such as dynamic systems, control theory, sensory feedback and information processing, electromechanical design, and real time software development.

The specialisation track objectives for Robotics and Control are:

The student will learn the theories, technologies, and methodologies used in modern robotics and control systems

The student will gain hands-on practical experience and technical skills in implementing robotics and control methods to solve real-life problems

The student will understand the different aspects needed to develop robotic and intelligent systems, and to use them to create innovative solutions and solve societal challenges.

In this specialisation, the first two courses focus on the fundamentals of modern robotics and control systems. The course "ACIT4810 - Advanced Methods in Modelling, Simulation, and Control" provides the mathematical foundations to understand, analyze, and implement modern control systems. This includes data driven dynamic modelling, multivariable and predictive control algorithms, and the combination of traditional control theory and AI-based methods. The course "ACIT4820 - Applied Robotics and Autonomous Systems" provides a hands-on overview of common theories and methods used in the design of robotic and autonomous systems. This includes state estimation, navigation, motion planning, computer vision, and implementation using Robot Operating System (ROS).

The specialisation course aims at providing an arena where students can learn about specific technologies and methods that are relevant for their master project. Suggestion for these themes can be varied from special applications within robotics and control theory, Applied AI methods and Machine Learning, IoT (sensor/ actuator) systems for both autonomous vehicles and distributed systems, embedded systems, and industrial process control to name a few.

The course "ACIT4020 - Robotics and Control Project" provides a hands-on experience with the application of novel theories and methods into a specific system in robotics and control.

There is a range of relevant specialisation courses from other tracks that can be suitable for Robotics and Control students. For instance, "ACIT4310 - Applied and Computational Mathematics", "ACIT4420 - Problem solving with scripting", "ACIT4630 - Advanced Machine Learning and Deep Learning", "ACIT4040 - Applied Artificial Intelligence Project", "ACIT4015 - Internet of Things", "ACIT4510 - Evolutionary AI and Robotics", "ACIT4720 - Medical Sensors and Actuators", "ACIT4740 - Microelectronic Circuits and Systems", "ACIT4030 - Machine Learning for 3D Computer Vision", and "ACIT4080 - Intelligent User Interfaces".

Recommended, but not required, prior knowledge

Basic knowledge on Electronics

Basic knowledge on Control Systems and mathematical modeling

Basic knowledge in Calculus, Statistics, and Linear algebra

Basic knowledge on programming

Universal Design of ICT

Specialisation courses (SPEC)

ACIT4910 - User Diversity and ICT barriers (1st Semester)

ACIT4920 - Universal Design of Interactive Systems (1st Semester)

ACIT4930 - Interaction Styles and Technologies for Accessibility (2nd Semester)

This specialisation focuses on identifying disabling ICT barriers and developing universally designed ICT solutions that can be used by as many people as possible, including people with disabilities, so that all citizens can take an active part in social activities, education and employment. This combines an understanding of diversity among users, situations and equipment, human-computer interaction, assistive technologies, and methods for universal design of ICT solutions, as well as knowledge of relevant national and international legislation, guidelines and standards.

With an emerging e-society, it is becoming essential that all electronic information and services are accessible for all, regardless of the device, the situation, or the abilities of the user. In Norway and many other countries, providing ICT solutions accessible for as many people as possible is becoming a legal requirement. This poses great challenges for competent ICT professionals and society's ICT infrastructure and services. This specialisation aims to meet the growing need of society for knowledge and expertise in universal design of ICT solutions such as web and mobile applications, e-services, e-commerce and self-service machines.

The specialisation track objectives for Universal Design of ICT are:

The student will acquire advanced knowledge of universal design and specialist knowledge of ICT, and learn how to analyze problems and solutions based on the history, traditions, characteristics and societal context of universal design and ICT

The student will gain skills in evaluating usability and accessibility of existing ICT systems and develop ICT solutions that are accessible and usable for as many people as possible

The student will understand how universally designed ICT solutions can positively affect a person's opportunities for actively taking part in a digitized society and can communicate this to both specialists and the general public

In this specialisation, the first two courses focus on the fundamentals of universal design of ICT. In the course "ACIT4910 - User Diversity and ICT barriers", topics covered include differences in user requirements due to diversity among users, situations and devices, as well as how to identify disabling barriers. National and international guidelines, regulations and legislation relevant to universal design of ICT are also covered. In the course "ACIT4920 - Universal Design of Interactive Systems", topics covered include the design of cost-effective prototypes, how to involve and communicate with users in the design process, and evaluating prototypes through user testing with diverse users.

In the second semester, the course "ACIT4930 - Interaction Styles and Technologies for Accessibility" focuses on technology and methods within human-computer interaction and available computer systems, including topics such as multimodal user interfaces and issues in interactions related to context, such as accessibility in public spaces, mobility problems, and the user's affective state.

The following electives are suggested: “ACIT4090 Globalization of Technology”, "ACIT4080 Intelligent User Interfaces" and "ACIT4045 Projects in Human Computer Interaction". This specialisation can be also be supplemented with other specialisation courses from other tracks such as Agile Service Management and Developer Operations or Problem solving with scripting as well as ACIT4025 Seminar in Cyber Security and privacy.

Recommended, but not required, prior knowledge:

Human-computer interaction and interaction design

Inclusive design

Universal design

User experience design

User-centred design

Short and long thesis

The thesis project is the keystone of the program for every candidate. Here, they will embark on an individual research project that is unique to them, their interest and specialisation. The program offers two options for the thesis project: a short and a long thesis. So-called external projects, where a company or organisation is a stakeholder in the project are also possible under the right circumstances. In all cases, the project proposal will go through a quality assurance process and the student will be assigned a local supervisor.

The short thesis project is 30 ECTS and will be in the final semester of the program. The topics for these projects can be initiated by students or be selected from a list of available projects offered from the faculty. Students are generally recommended to select a short thesis if they prefer to increase their breadth with more elective courses and find it more suitable for them to focus on the thesis in a single semester.

During the short thesis project, the student will give a mid-term presentation to report on their progress and solicit feedback from a larger group than their immediate partners and supervisors. This will also provide assurance that all students are on track.

The long thesis is 60 ECTS and therefore half of the entire time spent in the program. In addition, the project work is divided over more than two semesters allowing for a maximum time to reflect upon the work. In the final semester, all the time is focused on the thesis project, just like the short thesis. Long thesis projects go deeper into a single topic and should only be embarked if there is ongoing research in that specific topic at any of the research groups involved in the program in order to secure adequate supervision and quality. One will expect the candidate to become a participant of one of the research groups associated with the program and see their project as a part of a larger research effort at OsloMet. Students can therefore not propose their own long thesis project unless it is in collaboration with a faculty member and research group.

A long thesis is recommended for students who enjoy working independently for longer periods and who target an academic career later. Even though there is no formal difference with a long and short thesis with regard to qualifying for a PhD scholarship, the long thesis project has additional requirements with regard to writing a scientific paper as part of their project. A potential publication would normally be an advantage when applying for a PhD scholarship.

The long thesis project is divided into three phases, which are organized as separate courses. This structure ensures that there are concrete deliverables during the entire thesis project and not just at the end. During the first phase, students are to complete a literature survey as well as develop a suitable problem statement and approach for the project. In the second phase, much of the data gathering and development will take place, which requires the student to showcase their results and preliminary analysis. In the final phase, most of the writing takes place and the student will deliver a final thesis along with a research paper. For more details, please consult the course descriptions for these phases further down.

Elective courses

ACIT offers several elective courses that have their origin in one of the specialisation tracks, but can be of interest to all students. The elective courses can create interesting and complementing combinations of knowledge and skills for the individual student based on their particular interest. For many, they may give a necessary depth in a topic that they want to focus on in the thesis project later.

Elective courses are in principal only available for students who elect a short thesis structure rather than a long, since in the long thesis most of the time will be spent on the project. In broad terms, the elective courses offer more breadth with three extra courses while long thesis offers more depth into a single topic and it is up to the individual student to elect their most suited plan. Students do not have to decide on the elective courses they want to take at the beginning of the programme but can wait until their interests mature.

Not all elective courses are available at any time. Whether an elective course is run depends on the overall student interest and semester. Students are not guaranteed that an elective course will be offered if the number of assigned students is low. The faculty will work together with the students to collect interest in the specific courses in good time for the students to make adequate choices.

Students can in principle use courses from other MSc programs at the Faculty of Technology, Art and Design or external institutions as elective courses provided they have a relevance to ACIT's overall profile. This will allow students to explore other professional perspectives that normally interact extensively with the design, development and use of technology. The student has to investigate possible courses and apply the program council for approval in good time, generally in the middle of the preceding semester. Whether the student is granted access to the course depends on the availability at the other program and if the sufficient prerequisite knowledge is met.

Valgfritt emne Løper over flere semestre

1. studieår

Common courses

1. semester

Masters Thesis, long 60 ECTS

2. semester

Universal Design of ICT

Cloud-based services and operations

2. semester

Data Science

2. semester

Mathematical Modelling and Quantum Technologies

1. semester

2. semester

Applied Artificial Intelligence

2. semester

Robotics and Control

2. semester

Biomedical Engineering

1. semester

2. semester

Elective courses

Cyber Security

1. semester

2. semester

Electronics and Biomedical Systems

1. semester

2. semester

2. studieår

Applied Artificial Intelligence - Alternative specialisation course

Biomedical Engineering - Alternative specialisation course

Cloud-based services and operations - Alternative specialisation cours

Data Science - Alternative specialisation course

Mathematical Modelling (...) - Alternative specialisation course

Robotics and Control - Alternative specialisation course

Universal Design of ICT - Alternative specialisation course

Masters Thesis, short 30 ECTS

4. semester

Masters Thesis, long 60 ECTS

3. semester

4. semester

Elective courses

Cyber Security - Alternative specialisation course

Electronics and Biomedical Systems - Alternative specialisation course

Arbeids- og undervisningsformer

  • Revisjon godkjent av studieutvalget ved LUI 06.04.2017
  • Revisjon godkjent av prodekan for studier 26.06.2017
  • Redaksjonelle endringer 31.11.2017

Internasjonalisering

Spending a semester abroad is an opportunity for students to experience a different culture.

During a stay abroad, students are expected to take a full semester of courses at the external institution and incorporate them into their own ACIT education. For the ACIT program, the third semester is designed to offer an opening for internationalisation. Only students who plan to do a short thesis are eligible to travel abroad for a whole semester. Long thesis students are not eligible for a full semester abroad as they already have 20 ECTS of their schedule allocated to their master’s thesis in the third semester.

During the third semester, short thesis students will take two elective courses in addition to the Alternative Specialisation course. This allows for a broader range of subjects to choose from at the exchange institution as the electives do not necessarily have to be directly linked to the specialisation track. The Alternative Specialisation course, on the other hand, must be from an adjacent technological field. The student themselves will have to find courses that will function as substitutes for both the Alternative Specialisation and elective courses. Students are advised to explore the partner institutions listed in the link below to see which courses they think fit their background and interest. This could be courses within computer and information technology, including electronics, mathematical modelling and user-centered topics. The program's International Coordinator will review and approve the substitution of courses.

In the fourth semester, short and long thesis students may apply to carry out parts of their master’s thesis abroad. In such cases, students must apply to the ACIT Program Council for approval to travel abroad no later than the end of the third semester.

Requirements:

An average grade C in previously completed courses and a complete study progression for the two previous semesters.

An exchange agreement with the desired university or college must be in place before the student can apply.

Acceptance from a receiving professor or institution to an exchange-stay with the necessary academic relevance.

Information about requirements to travel abroad for an exchange semester:

https://student.oslomet.no/en/slik-soker-du

Arbeidskrav og obligatoriske aktiviteter

A coursework requirement is a compulsory piece of work/activity that must be approved before the student may take an examination. Coursework requirements are assessed "approved" or "not approved".

Not approved coursework requirements

Legitimate absence based on, for example, a medical certificate, does not exempt students from meeting the coursework requirements. Students who, due to illness or any other documented legitimate absence, do not meet the coursework requirements within the appointed deadline, should as far as possible be given a new attempt to meet the requirements before the relevant examination. An agreement with the relevant lecturer must be made in each individual case.

If, due to the nature of the subject/course, it is not possible to implement a new attempt to meet the requirements before the course exam, the student must expect to submit the coursework requirements at the next possible submission deadline. This may lead to a delay in progression through the Master's programme.

If a work requirement is assessed “not approved”, students have two chances to retake the work requirement. A work requirement that is assessed “not approved” three times, will result in loss of the right to take the course exam.

Mandatory attendance

In courses that require mandatory attendance, students must meet the minimum attendance requirement to pass the course. Failure to meet the minimum requirement will result in a loss of the right to take the course exam.

In cases where a student have a valid reason for absence due to illness or other legitimate reasons that can be documented, the teacher is responsible for making compensatory arrangement in order for the student to catch up on what he/she has missed. This could for example be a one-on-one tutorial or written assignment.

The administration processes all applications for exemptions.

Vurdering og sensur

Provisions governing examinations are laid down in the Act relating to Universities and University Colleges and the Regulations relating to Studies and Examinations at OsloMet.

Assessment methods vary between courses. They include written reports, portfolio assessments, written exams, oral presentations and oral exams.

A portfolio assessment provides an overall assessment awarding one grade for the whole portfolio. Students may only appeal against the determination of the examination grade awarded for the whole portfolio. Any information on weighting of grades must be considered as supplementary information in connection with the final grade. If the portfolio consists of elements such as an oral presentation, practical work etc., the examination result cannot be appealed against. The right to appeal is stated in the individual course descriptions.

If the examination in a course consists of more than one part, all parts of the examination must be passed in order to pass the course.

Normally each course has two internal examiners to assess students' work. Each semester one course will be chosen to include an external examiner, thus the students' work will be assessed by one external and one internal examiner. The Master's thesis is assessed by the two external examiners. Guidelines for master's theses at the Faculty can be found here: Retningslinjer for masteroppgaver ved Fakultet for teknologi, kunst og design - Student - minside (oslomet.no)

Øvrig informasjon

Quality assurance

The purpose of OsloMet's quality assurance system is to strengthen students' learning outcomes and development by raising the quality at all levels. Cooperation with the students, and their participation in the quality assurance work, is decisive to the overall learning outcome. Among the overall goals for the quality assurance system is to ensure:

  • that the educational activities, including practical training and the learning and study environment, maintain a high level of quality
  • that the study programmes are relevant for the professional fields
  • that the quality development continues to improve

For the students, this entails, among other things, student evaluations in the form of:

  • course evaluations
  • annual student surveys for all of OsloMet

More information about the quality assurance system is available here: https://student.oslomet.no/regelverk#etablering-studium-evaluering-kvalitetssystem

Programme supervisor scheme

The programme supervisor scheme is part of the quality assurance of each individual study programme. A programme supervisor is not an examiner, but someone who supervises the quality of the study programmes. All study programmes at OsloMet shall be subject to supervision by a programme supervisor, but there are different ways of practising the scheme. Reference is made to the Guidelines for Appointment and Use of Examiners at OsloMet: https://student.oslomet.no/retningslinjer-sensorer