Master's Programme in Applied Computer and Information Technology Programplan

The Master's program in Applied Computer and Information Technology (ACIT) offers an expert-level education in the design, development, use and maintenance of computer technology, electronics and software in areas that have become of great importance for modern societies. We live in a world with computing devices both surrounding us and, in some cases, even working inside us. Technology is a part of how we entertain ourselves, communicate, govern and heal. Services that span the world open up for individuals to interact across the globe.

Yet with technology comes new challenges. The application of computers and electronics in our society offers progress for many, but it may also close the doors for people with impairments. We can communicate across the globe, but our communication can be intercepted and used against us. Our data can be used to get new insight about our behavior, but the analysis is complex and requires ethical considerations of whether the search for new knowledge is indeed with the right intentions. Artificial Intelligence offers to delegate many mundane tasks to robots, but consequences are potentially wide and may trigger deep changes in our civilization.

The Faculty of Technology, Art and Design at Oslo Metropolitan University believes that solving these challenges requires a broad and multidisciplinary approach. Solutions for the public should be viewed as an artefact beyond a singular discipline, like Computer Science or Electrical Engineering. It needs to be a combination of expert knowledge and interdisciplinary thinking. Our researchers know from their own experience that in the real world, engineers sit alongside mathematicians, programmers, economists, sociologists, physicists, designers and statisticians, just to name a few, to work on self-driving cars, computer games, medical devices, solutions to combat the climate crisis.

As technologists we can become the enablers of others. We can let teachers teach in novel ways. We can let children with disabilities partake in activities previously denied to them and we can let doctors perform surgery on patients that are miles away. Moreover, we become inventors and transformers as we understand what others need and have the expertise to know what is possible, or should be possible. This makes our field incredibly meaningful and important. This program offers a range of specialisations stemming from the overlap of three fields of research: Computer Science, Electrical Engineering and Mathematical Modelling.

The uniqueness of ACIT is that it offers a closer connection between all three fields and showcase how they are part of the same technological fabric of today's digital society. Thus, ACIT recognizes that candidates will have a better foundation for solving tomorrows challenges if a broader perspective is available to them. The aim is not, however, to create generalists, but to create experts in their own field who are also able to see the broad picture of how technology impacts society. These individuals contribute not only through providing deep knowledge and expert skills from a relevant field, but at the same time are able to partake constructively as members of interdisciplinary teams. The program is designed to allow the student to select an area of specialisation but also requires them to become familiar with a second area of their choice. In addition, the student will be trained specifically in the role as the expert member of a team.

Each field of specialisation represents an area where the application of software, data, computers and electronics has become necessary for modern society yet challenging to do in practice. These areas are still wide enough to allow for life-long careers as technology progresses. In addition, a Master's degree in science requires each candidate to have training in scientific thinking and research, enabling our candidates to pursue careers as scholars in academia as well as industry researchers, leading the way for new discoveries and scientific progress.

ACIT Specialisation areas

Our program offers several areas of specialisation. Each area connects the student to an active research group at the faculty. When applying for the program, the applicant needs to select what area of specialisation to join. Please note that each specialisation has a unique set of admissions requirements.

ACIT: Applied Artificial Intelligence

Recent discoveries in artificial intelligence have enabled computers and machines to perform many cognitive tasks better than humans, from self-driving cars to diagnosing diseases in seconds. The application of artificial intelligence methods is revolutionizing the way we work and live. This specialisation involves learning how complex systems are designed and used to make autonomous decisions. The students will have access to different types of robotics and intelligent systems that can be used to test their work. This area involves programming, robotics and mathematics.

ACIT: Electronics and Biomedical Systems

The need for innovation in the field of electronics and biomedical systems has never been so important as now. Neither has it ever been given so much attention from governments, organisations providing health care and the media. It is evident that to provide world class health care, the need for technology that helps efficiency and accuracy is essential. This specialisation will prepare the students for a professional career in companies related to new and existing health products. The students gain an interdisciplinary background but with a focus in electrical engineering and instrumentation.

ACIT: Cloud-based Services and Operations

Today's services need to be designed for thousands; even millions of users and require infrastructures and architectural designs beyond common webservers and databases. This specialisation area focuses on the practice of designing, developing and running massive-scale services and delivering software faster and with higher quality than before. We embrace the DevOps philosophy, in that developers should be better trained in automation and deployment and operations should build mechanisms for developers to thrive. It is highly relevant for anyone who wants a career as a software developer. The specialisation covers both infrastructure management and agile software delivery and automated testing and deployment, creating candidates with a practical competence in the entire cloud stack from the servers and clouds and all the way to the running service.

ACIT: Cyber Security

Cyber security ensures the proper and reliable function of digital systems. Its focus is the creation, maintenance and analysis of information security, data privacy data secrecy, the assessment of risks and their mitigation, and the reliable operation of digital processes. The ACIT cyber security specialisation educates master students in the areas of general information security, in defensive and offensive operations for security, in technical data protection and privacy, and in the political and societal implications of cyber security, such as, for example, information warfare and cyberwar.

ACIT: Data Science

The wealth of data produced by us and the things around us offer new knowledge that can be useful for both business and government. It can assist in public transport, health care as well as provide tailored market solutions. With all the data available to us, however, a special expertise is needed to organize and harness it so that useful knowledge can be extracted. This area offers a deep-dive into the storage and analysis of Big Data from a practical perspective. Data Science involves programming, use of advanced tools and infrastructures and statistics.

ACIT: Universal Design of ICT

With our emerging digital society, it is becoming essential that all electronic information and services should be accessible for all, regardless of devices, situations, and abilities. As progress moves us forward, no-one should be left behind. This poses a great challenge on ICT infrastructure and services in our society. Our world requires competent ICT professionals who can create universally accessible user interfaces that work for all. This specialisation offers a unique opportunity to become that professional.

ACIT: Mathematical Modelling and Quantum Technologies

Application of mathematics to describe our world is a central element of many areas of our every-day life. Physics, economics and meteorology are examples of disciplines where mathematicians work side-by-side with specialists to convert real phenomena into equations. When these equations are translated into program code to be executed in potentially massive computing clusters, simulations are generated that may be used for e.g. weather or economy forecasting. This area is characterized by development of mathematical models, application of sophisticated methods for analyzing and simulating the models as well as use of tools, programming and computational infrastructures. Students of this specialisation can expect to learn how their competence can be utilized in practice by the industry.

ACIT: Robotics and Control

Robotics and Intelligent Systems are steadily revolutionizing almost every aspect of our every-day life. From self-driving cars, autonomous ships, fully automated factories and drones that can deliver groceries. It is a field with tremendous expected growth and demand for skilled multidisciplinary professionals in the convergence of electrical, mechanical and software engineering. This specialisation provides a hands-on approach to the analysis, design, and control of robotic and autonomous systems.

Programme objectives

This program offers a practical-minded, profession-oriented specialisation, extending a bachelors in technology, computer and software engineering, electrical engineering and mathematics. Our goal is to educate and train candidates so as to make them fit to address the challenges of both professional life and scholarly enquiry within their specialisation as well as being a productive member of interdisciplinary teams.

Graduates from this program will:

• understand the role of their specialisation in organisations and society
• possess deep technical skills from their own specialisation that can be applied in a variety of real-life scenarios
• understand how their specialisation is part of a wider fabric of skills necessary to solve tomorrows challenges
• have a professional and ethical attitude towards their role in the workplace
• display creative thinking in real-life situations, leaning both on theoretical knowledge and on pragmatism
• plan and execute their work in a structured and independent manner, be it as professionals or as researchers in their field

The program offers career-defining specialisations that are closely tied with the industry. Focus is on building practical skills combined with scientific craftsmanship. Graduates from this program are attractive candidates for public and private sectors as well as non-profit organisations. Our target audience are individuals with a bachelor's degree who are interested in an expert role as well as the option to pursue an academic career either directly or later.

The different specialisations together provide for a wide field of recruitment and is therefore relevant for bachelor graduates from many engineering backgrounds as well as traditional natural sciences. Students from fields within IT, such as human-computer interaction, web- development or applied computer technology will also find suitable specialisations here.

Please consider the admission requirements for a detailed list.

Applicants will choose the desired specialisation track at the point of applying for the program. Admission to the program is based on two sets of requirements. The general admission requirements, which are the same regardless of track chosen, and the specialisation track requirements. Please take special note of the individual requirements of each specialisation track.

For each specialisation track, there is also a list of recommended prior knowledge, which can be found in the Content and Structure section, under "Specialisation Track Content". That list is not a formal admission requirement, but we encourage students to review it in order know what areas they might want to spend time preparing in before starting in order to avoid steep learning curves. The topics listed can be found as part of most university bachelor programs in technology and engineering. The student can use the list to inform any decision on elective courses in their bachelor studies that might best prepare them for their targeted specialisation in this program.

General admission requirements

In order to qualify for an international master's degree, the applicant must be able to document sufficient mastery of English. Please consult the current regulations at OsloMet for a complete overview: English proficiency requirements for master's - OsloMet

In addition to English proficiency, applicants must have completed a BSc or equivalent program with a grade average of C or better.

The master programme aims for a diverse group of students from many countries. To ensure even representation in each of the specialisations, if a country is overrepresented in applications (with the exception of applicants from Norway), the program reserves the right to assign a maximum of three students from each country to a specialisation.

Specialisation track requirements

In order to be qualified for their desired track, the applicant must comply with at least ONE of the requirements for that track. Each requirement is a combination of Bachelor's degree from a specific field with possible conditions for ECTS within certain topics.

Applied Artificial Intelligence

• BSc in Computer Science, Computer Engineering or Informatics
• BSc in Information Technology or other equivalent qualifications, which include at least 80 ECTS within the field of Computer Science
• BSc in Electrical Engineering with at least 10 ECTS of programming
• BSc in Mathematics or Applied Mathematics with at least 10 ECTS of programming
• BSc in Mechanical Engineering with specialisation in mechatronics, with at least 20 ECTS in programming

Electronics and Biomedical Systems

• BSc in Electrical Engineering
• BSc in Biomedical Engineering
• BSc in Mechanical Engineering
• BSc in Chemical Engineering
• BSc in Biotechnology Engineering
• BSc in Physics
• BSc in Computer Science, Computer Engineering or Informatics
• BSc in Statistics

And 25 ECTS mathematics and/or statistics

Cloud-based Services and Operations

• BSc in Computer Science, Computer Engineering or Informatics
• BSc in Information Technology or other equivalent qualifications, with at least 80 ECTS within the field of Computer Science
• BSc in Electrical Engineering with at least 10 ECTS of programming
• BSc in Mechanical Engineering with specialisation in mechatronics, with at least 20 ECTS in programming

Cyber Security

• BSc in Computer Science, Computer Engineering or Informatics
• BSc in Information Technology or other equivalent qualifications, with at least 80 ECTS within the field of Computer Science

You also need a minimum of 10 ECTS in data security or a similar technical topics, such as network security, information security, mobile security, applied cryptography, privacy-enhancing technology or computer security management.

Data Science

• BSc in Computer Science, Computer Engineering or Informatics
• BSc in Mathematics or Applied Mathematics with at least 10 ECTS in programming
• BSc in Physics with at least 10 ECTS in programming
• BSc in Statistics with at least 10 ECTS in programming
• BSc in other engineering subjects with at least 10 ECTS in mathematics, 10 ECTS in statistics courses and 10 ECTS in programming

Mathematical Modelling and Quantum Technologies

• BSc in an engineering discipline with at least 30 ECTS (in total) withinmathematics, statistics and/or scientific computing
• BSc in Computer Science or Informatics with at least 30 ECTS (in total) within mathematics, statistics and/or scientific computing
• BSc in Mathematics
• BSc in Statistics
• BSc in Physics

Robotics and Control

• BSc in Electrical Engineering
• BSc in Mechanical Engineering
• BSc in Chemical Engineering
• BSc in Physics
• BSc in Mathematics or Applied Mathematics
• BSc in Computer Science, Computer Engineering or Informatics

And 10 ECTS programming and 25 ECTS mathematics and/or statistics.

Universal Design of ICT

• BSc in Computer Science, Computer Engineering or Informatics
• BSc in Information Technology or other equivalent qualifications, which at least 80 ECTS within the field of Computer Science.

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

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.

The learning outcomes will be achieved by means of different learning methods adapted to each individual course. Teaching methods include lectures, assignments, seminars, project work and the use of online learning resources. Project work is carried out both in groups and individually. In some courses, lab environments are available for students to practice their skills. The labs will mimic the real world as closely as possible in order to allow for a realistic setting for the students.

The program is based on student-centered learning methods and project work that requires active participation from students. Students will receive feedback on their presentations and reports.

For seminar-based courses, it is essential for students to be prepared to follow the presentations and actively participate in projects and discussions.

Research and teaching are integrated throughout the study program. The teaching is constantly updated to encompass new knowledge, and research articles are part of the syllabus in many of the courses. Furthermore, the students will participate in research-related discussions and have the opportunity to be included in ongoing research and development through projects that are part of the study program.

The master's thesis is a piece of independent research or development work in one of the key topics of the study program. Each student will be assigned an internal supervisor, who will ensure that the project complies with research ethics principles and help students to formulate the research question and ensure quality in the collection and analysis of data. Seminars with supervisors and fellow students will develop each student's ability to critically assess and discuss their own and other students' work. The thesis shall be a written report based on research principles and methods.

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

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.

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)

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