Master's Programme in Industrial Analytics

120 credits

Do you want to develop the next generation of digital and sustainable industrial systems, based on expertise in both industrial engineering and data science? The Master's Programme in Industrial Analytics is unique in its kind and combines subjects such as systems analysis, data analysis, AI and simulation. You will learn about optimisation for analysis and design, as well as optimisation of complex technical systems and business processes. As a student, you will study in a highly current field where the need for competence is growing quickly.

Autumn 2023 Autumn 2023, Uppsala, 100%, On-campus, English

Autumn 2024 Autumn 2024, Uppsala, 100%, On-campus, English

Industrial systems constitute the foundation of our modern world. The ongoing digitisation of all industry operations means completely new opportunities that are often described as two new ongoing industrial revolutions.

  • “Industry 4.0”: Smart industrial systems characterised by increased efficiency and productivity with the help of digitalised information collected wirelessly and via cable/internet from subcontractors, warehouses, production, maintenance, delivered products, customer behaviour, etc.
  • “Industry 5.0”: Smart digitalised industrial systems that are long-term safe and generally sustainable for the employees as well as nature, society, and its individuals.

On an overall level, the interdisciplinary subject area of Industrial Analysis is based on the two subfields that are usually called Industrial Engineering and Computer Science. A central objective of the programme is therefore that you should gain a detailed understanding of, among other things:

  • production management and operations analysis/optimisation,
  • industrial statistics, data analysis, signal and image analysis, machine learning, and artificial intelligence,
  • large-scale data collection and management from sensors and actuators, databases, and “Internet of Things”,
  • analysis, design, simulation and optimisation of complex industrial systems and processes.

Professors and other doctoral candidates at Uppsala University who work in these areas are course leaders and lecturers within the programme. Therefore, you can be sure that you will learn a lot about the very latest and most promising methods and trends in industrial analysis. By giving you knowledge and skills in modern production processes and what modern computer and engineering science has to offer, the training will build your know-how in an area where the need for skills is growing very quickly.

Degree

The programme leads to the degree of Master of Science (120 credits) with 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. They use methods such as:

  • digital models,
  • simulation,
  • optimisation,
  • large-scale data management and data analytics,
  • artificial intelligence,
  • connectivity through the internet.

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.

Courses within the programme

See the programme outline for courses within the programme.

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. In a seminar, you present your ideas and discuss e.g. a course book, or other study material that you are required to read or write with your classmates. 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 stand out 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 learning. A large part of the programme is spent studying on your own or in a study group outside the classroom, and as such, you must take a proactive role in structuring your studies.

The language of instruction is English.

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.

Several reports from established organisations and companies have highlighted the demand for analytics. The reports have particularly emphasised a number of specialisations in digitalisation. These are e.g. data handling, data mining, AI, machine learning, and 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 a 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.

Contact

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