Digital Manufacturing (DM)

Digital Manufacturing (DM)

120 ECTS

Field of Study:
Computer Science and Information Technology

2 years, full-time

Hold a Bachelor of Science or be in the final year of studies of... (read more).

Tuition fees & scholarships:
For EU and non-EU citizens.
More information.

Language of Instruction:
More information.

Please observe that the Digital Manufacturing Master's Programme is undergoing EIT Label quality assessment. We will be able to award the EIT Label certificate to Digital Manufacturing graduate students once this assessment is complete.

Digital Manufacturing (DM)

Why study Digital Manufacturing at EIT Digital Master School?

This Digital Manufacturing (DM) Master’s Programme could be considered aligned with other initiatives at National and International level to develop and promote the implementation of digitalization technologies in EU industry, that could lead to an increase of productivity on every sector. A key factor on this process is going to be the engineering profile of the people that will lead this transformation, a real integrated curriculum among Industrial and Manufacturing technologies, together with computer science and telecommunications technologies. The aim of this Programme is to provide this truly integrated curriculum on student.

The EIT Digital Master’s degree DM is an interdisciplinary programme that combines generation and predictive use of data arising from the Industrial Assets, and the Computer Science tools to develop Decision Making and Artificial Intelligence for Industry.

“There is only one way to increase the efficiency of our strongly automated industrial processes, it is to take the advantage of data arising from them” - Dr. Juan J. Marquez, Digital Manufacturing Master Programme Coordinator

Who can apply?

If you wish to apply to this Programme you must have a Bachelor of Science in, or be in your final year of studies of:

  • Computer Science 
  • Mathematics
  • Statistics
  • Electrical Engineering
  • Mechanical Engineering

In special cases students from Industrial Engineering, Chemical Engineering can be considered

How is the programme structured?

All EIT Digital Master School programmes follow the same scheme:

  • Students study one year at an ‘entry’ university and one year at an ‘exit’ university in two of EIT Digital’s hot spots around Europe.
  • Upon completion, graduates receive degrees from the two universities and a certificate awarded by the European Institute of Innovation and Technology.
  • The first year is similar at all entry points with basic courses to lay the foundation for the chosen technical programme focus. Some elective courses may also be chosen. At the same time, students are introduced to business and management. During the second semester, a design project is combined with business development exercises. These teach how to turn technology into business and how to present a convincing business plan.
  • In between the first year and the second year, a summer school addresses business opportunities within a socially relevant theme.
  • The second year offers a specialisation and a graduation project. The gradation project includes an internship at a company or a research institute and results in a Master thesis with a strong innovation and entrepreneurship dimension.

To learn more about the I&E minor please click here.

Career Prospects

The Master’s education will provide you with a strong technical entrepreneur education. You will have the option to work closely with some of the top multinational companies in partnership with the EIT Digital, they will give you training in real projects, as well as mentoring to start your own business, valuable practical experience, and help you to develop your entrepreneurship skills.

Graduates from the DM master’s programme will qualify for jobs in international and local organizations in both technical and business roles. Typical titles are:

  • Industrial Internet of Things Expert. Application Engineer
  • Digital Manufacturing Application Designer
  • Edge Computing for Industrial Internet of Things
  • Artificial Intelligence on Industrial Applications
  • Advanced Robotics Applications for Industry
  • Product Manager, or Consultant

Where can I study Digital Manufacturing?

What can I study at the entry and exit points?

Entry - 1st year, common courses

Each Entry University in DM provides introductory courses, from Mechanical-Manufacturing, Advanced Robotics, Industrial Internet of the Things, Artificial Intelligence and Operation Technologies Cybersecurity Areas. These Areas are considered the core knowledge to develop the Factory of the Future on every industrial business.

The following courses are offered at UPM:

Factory Engineering for Programmers/ Programming for Factory Engineers
This is an elective oriented to balancing of Computer Science Engineering or equivalent tracks on Factory Engineering Knowledge (Industrial/Manufacturing), and Mechanical/Electrical/Industrial to programming background for Digital Factory Applications.

Advanced Robotics
This subject is focused on applying robotics arm manipulation and mobile platforms technologies to industrial processes. Applied robotics discusses topics related to mobile robotics (ground, aerial and water-underwater) vehicles, complex arm manipulation, and robotic software programming platforms, such as ROS and several simulation and designing tools.

Industrial Internet of the Things
The aim of this subject s to cover basic aspects of communication networks, and how to implement them from the point of view of the design of embedded systems on the edge.

Communication networks, wireless technologies and others, Embedded computing platforms, Embedded operating systems, Real Time Embedded systems.

Digital Manufacturing
This course is oriented to develop the basic knowledge on technologies like Product Lifecycle Management systems and Manufacturing Execution Systems, in order to produce valid Product and Production Digital Twin viable to improve productivity and efficiency in real applications, Plant Simulation Technologies will support optimization of the assets and also will allow gathering data to produce other advanced uses and applications.

Artificial Intelligence
The main objective of this course is the student to be able to apply the most important Machine Learning Techniques based on Artificial Neural Networks and be able to analyze their results and methodology when compare to classical statistical methods. The methodology is based on solving problems using actual data, some of them based on synthetic data, useful for getting familiar with the techniques, and some others based on data from real-word applications. During the course, we will go through Supervised and Unsupervised Neural Networks, culminating in Deep Learning Methods.

Budapest University of Technology and Economics (BME), Hungary

Budapest University of Technology and Economics (BME) was founded in 1782 under the name of Institutum Geometrico-Hydrotechnicum, has been the top higher education institution of Hungary and it also has well-established international reputation. You can find more info on BME at

The entry year of the DIGITAL MANUFACTURING Master Program is organized by the Faculty of Electrical Engineering and Informatics (BME-VIK). You can find more info on BME-VIK at

Detailed information about the DIGITAL MANUFACTURING Master Program offered by BME-VIK can be found at

Programme lead: Tamás Kovácsházy - 

Detailed course descriptions can be found at: 

The following compulsory major courses are offered in the Fall (1st) semester (11 ECTS):

  • Natural science I (see the list of offered courses later), 3 ECTS minimum
  • Design and integration of embedded systems, 4 ECTS,
  • Autonomous robots and vehicles, 4 ECTS

The following compulsory major courses are offered in the Spring (2nd) semester (19 ECTS):

  • Natural science II (see the list of offered courses later), 4 ECTS
  • Embedded systems security, 4 ECTS
  • Software technology for embedded systems, 4 ECTS
  • Advanced manufacturing, 5 ECTS
  • Project laboratory, 2 ECTS

The following optional major courses are offered (8 ECTS from two semesters):

  • IIoT and edge computing, 4 ECTS, Fall semester
  • Critical embedded systems, 4 ECTS, Fall semester
  • Software and systems verification, 4 ECTS, Fall semester
  • Process planning, 3 ECTS, Fall semester
  • Formal methods, 4 ECTS, Spring semester
  • Artificial intelligence based control, 4 ECTS, Spring semester
  • Computer vision systems, 4 ECTS, Spring semester

Natural science courses offered (7 ECTS is required minimum):

  • Measurement theory, 4 ECTS, Spring semester
  • Communication theory, 4 ECTS, Spring semester
  • Linear algebra, 3 ECTS, Spring semester
  • Combinatorial optimization, 3 ECTS, Spring
  • Stochastics, 3 ECTS, Fall semester
  • Applied Algebra and Mathematical Logic, 4 ECTS, Fall semester

Politecnico di Milano (POLIMI), Italy

Link to university website:

Responsible: Gianluca Palermo
Contact: Federico Schiepatti,

Technical Major (total ECTS = 21)

  • DATA BASES 2 - 5 ECTS, I semester
  • SOFTWARE ENGINEERING 2 - 5 ECTS, I semester 

Elective Courses (3 choices, total ECTS = 15)

  • EMBEDDED SYSTEMS - 5 ECTS, I semester 
  • SENSOR SYSTEMS - 5 ECTS, I semester 
  • MACHINE LEARNING - 5 ECTS, II semester 
  • ROBOTICS - 5 ECTS, II semester 
  • INTERNET OF THINGS - 5 ECTS, II semester 

I&E Minor - Innovation and Entrepreneurship courses (total ECTS = 24)

  • STRATEGY & MARKETING - 10 ECTS, I semester
  • I&E Summer School - 4 ECTS, II semester

Technical University of Madrid ETSII-UPM, Spain


Compulsory common (36 ECTS), I&E (20 ECTS)

UPM has a leading role in Mechanical, Manufacturing and Automation Eng. in Spain, 49 in QS Ranking on Mechanical and Manufacturing Eng. with research groups that are internationally recognized in the fields of Digital Manufacturing, Industrial Internet of Things, Artificial Intelligence applied to Industrial Robotics.

The School of Industrial Engineering at the Technical University of Madrid (UPM) from more than 160 years merges Research and Development for industry in the areas of Manufacturing, Automation and Industrial Electronics and Management offers a specialization in Digital Manufacturing to merge with Computer Science Techniques. In the context of Industrial Systems, integration of all the Product Lifecycle Data can now be certainly connected with real data arising from Products, Processes, Production Lines, and Operation Technologies. In the other hand there is a strong need to improve productivity and effectiveness. Automation Investment in the recent years has not been able per se to improve productivity, since most of processes are highly automated yet. Smart use and specific applications development will be needed in the coming years to improve productivity of highly automated plants, and to improve effectiveness. Low latency is very important in such processes to be applied in real time; thus edge computing will play a substantial role on the new developments.

First Semester


Second Semester


Summer Course

  • 4 ECTS Summer Courses on Innovation & Entrepreneurship

University of Twente (UT), The Netherlands

1st quarter  (15 ECTS)

3D printing               
Production technology at the core of smart industry         

Internet of Things     
Wireless sensor networks

I&E Basics: Innovation and Entrepreneurial Finance for EIT        
Basic theories in innovation management and entrepreneurial finance           

2nd quarter (15 ECTS)

Managing Big Data   
Programming solutions related to big data

Supply chain management and innovation           
Supply chain management, innovation, technology management

Business Development Lab I for EIT 1         
Integrate, illustrate key theories in innovation and entrepreneurship

3rd quarter (15 ECTS)

Image Processing and Computer Vision     
How image data can be used (to control production equipment)

Industrial Robotic Systems  
Designing automated production cells

Business Development Lab 2 for EIT 1        
Evaluate the quality of alternative designs of business models       

4th quarter (15 ECTS)

Machine Learning in Engineering   
Self-controlling and optimizing strategies for production systems

Security Services for the Internet of Things
Overview of IoT security challenges and solutions to address them

Virtual Reality          
Using data to look into production processes

Exit - 2nd year, specialisation

Tallinn University of Technology (TalTech), Estonia

Link to the university:


Specialisation: Artificial Intelligence and Embedded Systems

Innovation and Entrepreneurship module:
In this module the concepts related to entrepreneurship, R&D, and innovation are discussed during the course and students apply the obtained skills in the group work assignments.

  • I&E Study (6 ECTS)

24 ECTS Specialization elective courses (combined from the following modules):

Cyber Security:
Principles of cyber security and cryptography are discussed. Also, the courses focus on how to protect data when storing and communicating and how to ensure data integrity.

  • Foundations of Cyber Security (6 ECTS)
  • Cryptography (6 ECTS)
  • Cyber Security Management (6 ECTS)

Artificial Intelligence:
The courses cover a range of advanced topics in artificial intelligence. The topics and methodologies covered in these courses are used for complex identification and control system.

  • Intelligent Control Systems (6 ECTS)
  • Computer Vision (6 ECTS)
  • Machine Vision (6 ECTS)

Data Management:
The courses give a deeper insight into the means and methods to gather, transfer, and analyse data depending on energy, integrity, security, and other relevant requirements.

  • Data Mining (6 ECTS)
  • Data Acquisition Means and Methods (6 ECTS)
  • Applied Data Communication (6 ECTS)

Embedded Systems and IoT:
In the final module, the computation and communication using distributed embedded systems are discussed. An additional focus on the concept of Internet-of-Things for industry is analysed and looked into.

  • Basics of Embedded Systems (6 ECTS)
  • Internet of Things for Industry (6 ECTS)
  • Networks of Smart Things (6 ECTS)

University of Turku (UTU), Finland

University website:

Contact: Dr Juha Plosila,

Specialisation: Data Analytics at the Edge

UTU provides an exit year specialization on real-time sensor data analytics in the digital factory/manufacturing context. It will include a large industry-driven capstone project (multidisciplinary group work) as a recommended elective course with shipbuilding or another relevant branch of manufacturing as a focus area. Turku is well known especially for its thriving shipbuilding and marine engineering industry.

More information about the Turku Business Region can be found at    


Innovation & Entrepreneurship Study (6 ECTS)

Specialization elective courses (select 25 ECTS from the following list): 

  • Capstone Project (10 ECTS)
  • Data Analysis and Knowledge Discovery (5 ECTS)
  • Applications of Data Analysis (5 ECTS)
  • Machine Learning and Pattern Recognition (5 ECTS)
  • Analytics for Industrial Internet (5 ECTS)
  • Autonomous Systems Architectures (5 ECTS)
  • Deep Learning (5 ECTS)
  • Perception and Navigation in Robotics (5 ECTS)
  • Machine Learning and Algorithmics Seminar (5 ECTS)
  • Robotics and Autonomous Systems (5 ECTS)
  • System Modelling and Synthesis with HDL (5 ECTS)
  • Hardware Accelerators for Robotics and AI
  • Sensors and Interfaces (5 ECTS)
  • Multidimensional Sensing Techniques (5 ECTS)
  • Autonomic Software and Systems (5 ECTS)

Master’s Thesis (30 ECTS)

Eötvös Loránd University (ELTE), Hungary

Link to the university: 
Contact: Dr. Matyas Ando; 

Specialisation: Communications and Optimization in Digital Manufacturing

The ELTE Faculty of Informatics has great competence both in computer science and in mechanical engineering. Courses within the Digital Factory programme will be supported by hands-on experiences with CNC machines, PLC controlled assembly lines, as well as robots. Thanks to our core infrastructure, we are able to teach Industry 4.0 on a project-oriented basis. In particular, we focus on communication channels and data-driven optimization. Detailed information on infrastructure is available here (,

Technical major (24 ECTS):

Digital Factory Lab I. II. (5+5 ECTS): Personalized project task – taking into account prequalification and interest. The project task is related to the machining processes (CNC systems) or assembly line (PLC, Robot), where the data collection and processing is essential. The aim is that students meet with industrial problems and create appropriate solution for it with the help of the supervisor.

Hardware based programming (5ECTS): The aim of this subject is to cover basic aspects of hardware resources, and how to utilize them from the point of view of the design of embedded systems. The subject will focus on MCU hardware architectures, low-level MCU programming (instruction set, machine code structure, Assembly), accessing, configuring and programming internal hardware units (oscillator, prescalers, power options, WDT, I/O ports, ADC, timers & PWM modes, interrupts, fuse and lock bits) using low- and/or high-level programming languages, and exploiting wireless technologies in embedded devices. During the lectures the students will learn about the hardware resources, their architecture, general and special properties, and operational modes. During practical lessons the student not just learn how to utilize these resources, but also how to build small multinode systems for practical purposes.

Data mining (5 ECTS): This course helps student to acquire a deep understanding on the most important fields and algorithms of data mining. The concerned topics are data mining basics, knowledge discovery process, data preparation and data cleaning, similarity and diversity metrics, curse of dimensionality and dimensionality reduction, cluster analysis, classification, frequent itemset mining, association rules and anomaly detection. In order to achieve a deep insight, the course material also provides practical examples with data acquired from various sources.

Elective courses (4 ECTS)

Innovation and Entrepreneurship major (6 ECTS):

I&E Study (6 ECTS): Applying, synthesizing, and evaluating prior innovation and entrepreneurship learning in the context of a specific technology. The course provides differentiated professional skills to the accomplishment of the innovation and entrepreneurship study (I&E study) related to the technical thesis. The course aims the preperation of an I&E study which analizes the business opportunities of the described idea or business process. The teacher evaluates the study.

Master thesis project (30 ECTS)

The first semester studies will be located at the ELTE Savaria Campus in Szombathely, while the internship opportunity of the second semester, based on which the thesis will be grounded, will be in Budapest or Szombathely at an Industry 4.0 partner. During this period students can actively be part of the Budapest Co-location Centre community, having their base and extra curriculum activities here.

University of Bologna (UNIBO), Italy

University website 

Contact: Prof. Marco Di Felice, 

Specialisation: Internet of Things and Artificial Intelligence for Digital Innovation in Manufacturing

The Department of Computer Science and Engineering of the University of Bologna has a strong expertise on artificial Intelligence, data analytics, cybersecurity and networking for IoT systems, and it is involved in several joint research projects with regional industrial partners on the digital transformation and innovation in Industry 4.0 scenarios. The proposed specialization aims at providing a solid deepening on networking, IA and data management techniques with a clear focus on technologies, applications and research issues for the Manufacturing 4.0.

Innovation and Entrepreneurship major (6 ECTS)

  • Ethics in Artificial Intelligence

Final examination (24 ECTS)

Mandatory courses (6 ECTS) 

  • Natural Language Processing (6 ECTS)

Elective courses (24 ECTS) 

  • Architecture and Platforms for Artificial Intelligence (6 ECTS)
  • Artificial Intelligence in Industry (6 ECTS)
  • Blockchain and Cryptocurrencies (6 ECTS)
  • Internet of Things (6 ECTS)
  • Multi-Agent Systems (6 ECTS)
  • Complex Systems & Network Science (6 ECTS)
  • User Experience Design (6 ECTS)
  • Data Mining, Text Mining and Big Data Analytics (6 ECTS)
  • Multimedia Data Management (6 ECTS
  • Knowledge Engineering (6 ECTS)

University of Twente (UT), The Netherlands

UT’s track will prepare students for a role as innovation manager within companies, supervising the transformation to smart industry based manufacturing strategies. He/she will be able to take on that role based on broad view of the working field combined with expert knowledge  on manufacturing hardware and technologies data management and security and business strategies.


Innovation & Entrepreneurship Study (6 ECTS)

Specialization elective courses (select 25 ECTS from the following list):

  • Maintenance Engineering & Management              
  • Modelling of Technical Design Processes                                        
  • Plastic and Elastomer Engineering               
  • Governing Product Development                            
  • Sources of Innovation
  • 3D Printing
  • Modern Robotics
  • Big Data
  • Algorithms, Data structures & Complexity
  • Data Science                          
  • Data Science Additional Topics                    
  • Managing Big Data               
  • Secure Data Management    
  • Foundations of Information Systems
  • Foundations of Information Retrieval
  • Cyber Risk Management
  • Cyber-Physical Systems
  • Cybersecurity Management
  • Cyber Data Analytics
  • Economics of Security
  • Software Security

Master’s Thesis (30 ECTS)

Application Period 2 Deadline: 12 April 2021 17:00 CEST

Have questions? We are here to help!

Digital Manufacturing (DM)
120 ECTS
Field of Study:
Computer Science and Information Technology
2 years, full-time
Hold a Backelor of Science or be in the final year of studies of... (read more).
Tuition fees & scholarships:
For EU and non-EU citizens.
More information.
Language of Instruction:
More information.

Please observe that the Digital Manufacturing Master's Programme is undergoing EIT Label quality assessment. We will be able to award the EIT Label certificate to Digital Manufacturing graduate students once this assessment is complete.

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