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 contribute to the industry of the future.
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.
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. This may be through modelling, simulation and optimisation of industrial systems, AI and machine learning, large-scale data management and analysis, the Industrial Internet of Things (IIoT) and systems architecture.
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.
In addition, the programme integrates both theoretical and practical knowledge based on the latest research in industrial analytics. 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. As a student in the programme, you will receive a detailed understanding of production management, operational analysis and computer science for the development and maintenance of modern industrial systems.
You will also study in close proximity to the latest research within industrial analytics. 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 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, 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 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.
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 people 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.
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, for instance in technical physics with specialisation in industrial engineering or computer science. Additional PhD study subjects may also be available at UU or other universities.
Career support During your whole time as a student UU Careers offers you support and guidance. You have the opportunity to partake in a variety of career activities and events, as well as receive individual career counselling. This service is free of charge for all students at Uppsala University. Read more about UU Careers.
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 All applicants need to verify English language proficiency that corresponds to English studies at upper secondary (high school) level in Sweden ("English 6"). This can be done in a number of ways, including through an internationally recognised test such as TOEFL or IELTS, or through previous upper secondary (high school) or university studies. The minimum test scores are:
IELTS: an overall mark of 6.5 and no section below 5.5
TOEFL: Paper-based: Score of 4.5 (scale 1–6) in written test and a total score of 575. Internet-based: Score of 20 (scale 0–30) in written test and a total score of 90
a total appraisal of quantity and quality 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.
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