Do you want to develop the next generation of industrial systems and gain unique expertise in both industrial engineering and computer science? Whether your background is in engineering or computer science, the Master's Programme in Industrial Analytics will provide you with the skills to raise in your career in the industry of the future.
Why this programme?
The Master's Programme in Industrial Analytics is a unique interdisciplinary programme in industrial engineering and computer science. Unlike most industrial engineering programmes, it also includes data analysis, design and optimisation of complex technical systems from a life cycle perspective. The programme also combines technology and management, which you will learn more about to be able to develop and optimise systems within various industrial domains such as manufacturing, medtech and healthcare systems.
Industrial systems are the foundation of our modern world. Today, society faces great challenges that drive demand for the renewal of industry through digitalisation, with the goal to improve efficiency, productivity and sustainability. Due to this, the use of data analytics and informatics for the design, analysis, optimisation and decision making in industrial systems and processes is growing more common. As a student in the programme, you can expect to gain a comprehensive understanding of how you can use operations management, operational research and computer science for the successful development and operation of modern industrial systems.
By providing you with knowledge and skills in production processes and the methods and solutions offered by IT, the programme will expand your skill set in an area with growing demand for qualified applicants, both in the industrial sector and society at large. You will receive a detailed understanding of production management, operational analysis and computer science for the development and maintenance of modern industrial systems.
Industrial analytics is a subject that encompasses industrial engineering, information technology and management. The field incorporates several parts of the Industry 4.0 paradigm, an umbrella term for methods and concepts that aim to make the industries of the future smarter. Research teams at Uppsala University currently investigate subjects such as machine learning and AI, the Internet of Things, sensor systems, data simulation and analysis, image analysis and prescriptive analysis of production systems. Professors and other academics in these research groups are course directors and lecturers in the programme, and as such, you can be sure to receive up-to-date knowledge and instruction in these subjects.
Student Profile You are someone with not only a background in engineering or computer science, but also a strong interest in correlated fields of technology and management. Moreover, you also have an internal drive for problem solving and improving systems and modern industrial processes through the use of industrial analytics.
The programme leads to a Master of Science (120 credits) with either Industrial Engineering and Management or Computer Science as the main field of study.
The Master's Programme in Industrial Analytics comprises a set of courses that result in a Master's degree in industrial engineering or computer science. The choice between these two specialisations comes down to which courses you opt to take and are eligible for. As such, the programme has two main tracks: one oriented toward industrial engineering, and one toward computer science.
The programme intersperses industrial engineering courses with information technology courses throughout every semester. In addition, orientating and theoretical courses are combined, where methods such as digital models, simulation, optimisation, large-scale data management and data analytics, artificial intelligence and connectivity through the internet are used.
The programme concludes with a degree project of 30 credits, which can be done internally within any of the research groups of the Department at Uppsala University, or externally within the private sector.
At several points during the programme, you will be able to engage with the world outside the classroom and have the opportunity to apply your knowledge in practical situations. As part of the project courses and the exam course, you will be faced not only with engineering and industrial challenges, but also with economic and organisational ones, to which you will be expected to find practical solutions.
The teaching consists of lectures, practical assignments, group exercises, labs, seminars, projects and field trips. The focus is on applied knowledge for industrial applications. We make use of IT tools and software packages that are common in the industry. Proficiency in these tools will be highly useful for your future employment.
For the group exercises, you will complete them together with your classmates outside the classroom. This way, you learn from each other and you train to be a team player. On a seminar, you present your ideas and discuss with your classmates regarding e.g. a course book or other study material that you are required to read or write before the seminar; while the teacher usually only moderates the discussion. All the students are expected to be active participants in all forms of discussions. The aim is to develop critical thinking and collaborative skills. Both the capabilities to work in teams and think critically will make you standout in your career development.
The teachers in the programme are active researchers with extensive expertise in their fields. Also, close ties with the industry are ensured in the form of field trips, guest lectures and various projects, where you will meet professionals with considerable experience in system improvement, analytics and manufacturing outside the University.
As a student in the programme, you are expected to actively contribute to teaching sessions while also assuming responsibility for your own learning. A large part of the programme is spent studying on your own or in a study group outside the classroom, and as such, it is important that you take a proactive role in structuring your own studies.
The labour market for candidates with qualifications in industrial analytics is projected to be excellent both nationally and internationally. Technology and knowledge-intensive companies have a large need for well-trained professionals with skills in engineering and computer science who understand the possibilities that industrial analytics offer industrial system development. With qualifications in these two areas, you will be at an advantage in their hiring processes anywhere in the world.
A number of reports from established organisations and companies have highlighted the demand in analytics. The reports have particularly emphasised a number of specialisations in digitalisation such as data handling, data mining, AI, machine learning, application development, but also "softer" aspects such as production management, sales, and innovations.
Upon completion of your degree, you may choose to remain in academia and pursue a PhD degree, for instance in technical physics with specialisation in industrial engineering or computer science. Additional PhD study subjects may also be available at Uppsala University or other universities.
Career support During your time as a student, UU Careers offers support and guidance. You have the opportunity to take part in a variety of activities and events that will prepare you for your future career. Learn more about UU Careers.
Below you will find the details about eligibility requirements, selection criteria, and tuition fees. For information on how to apply and what documents you need to submit, check the application guide. For this programme, besides the general supporting documents, you also need to submit one programme-specific document: a statement of purpose.
Requirements: Academic requirements A Bachelor's degree, equivalent to a Swedish Kandidatexamen, from an internationally recognised university. Also required is:
90 credits in mechanical engineering, industrial engineering, production engineering, automation engineering and/or computer science/information technology;
5 credits in computer programming;
20 credits in mathematics;
5 credits in statistics and probability theory.
Language requirements Proficiency in English equivalent to the Swedish upper secondary course English 6. This requirement can be met either by achieving the required score on an internationally recognised test, or by previous upper secondary or university studies in some countries. Detailed instructions on how to provide evidence of your English proficiency are available at universityadmissions.se.
Students are selected based on:
an overall appraisal of previous university studies; and
a statement of purpose (1 page).
Tuition fee-paying students and non-paying students are admitted on the same grounds but in different selection groups.
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees. Fees cover application and tuition only and do not cover accommodation, academic literature or the general cost of living. Read more about fees.