Machine Intelligence and Data Science (MIND)

Education / Technology

Are you looking for a programme where you get to take on real-world challenges and design solutions? Would you like to learn a broad set of techniques for dealing with data of various types? Then now is the time to take a leap forward in your career and apply to the master’s degree programme Machine Intelligence and Data Science (MIND)!

  • Degree title
    Master of Engineering
  • Delivery method
    Hybrid (on-campus and online)
  • Level
    Master's programme
  • Language
    English
  • Scope
    60 ECTS
  • Education duration
    1 year
  • Entry requirements
    In order to meet the eligibility criteria, applicants must have a suitable bachelor's degree in information technology, computer science, natural sciences or business (with a minor in IT or CS) or a similar field deemed to include sufficient technical skills and scientific rigor, and a minimum of two years (24 months) of relevant work experience gained after the completion of the bachelor's degree.

Emmanuel Raj
graduate (2020), Big Data Analytics (The former Big Data Analytics has transformed into MIND)

Emmanuel Raj, Big Data Analytics graduate
Big Data Analytics gave me a platform to learn practical skills in data science and ML Engineering, and excel by applying them in the industry and challenge the state of the art in academia. The programme equipped me with critical thinking skills to do research and development as well as solve industry problems at the same time. I recommend this master's degree programme to level up your data science skills.

Salvatore Della Vecchia
graduate, Big Data Analytics (The former Big Data Analytics has transformed into MIND)

Alumnus Salvatore Della Vecchia
Gaining the latest knowledge helps both my own career development and my employer. I am particularly happy with the link between research and education offered at Arcada and how the latest competencies have been incorporated into the courses.

Programme

Machine Intelligence and Data Science (MIND) gives you an in-depth understanding of how to make use of data in order to create insights. This master's degree programme is arranged so that you rapidly gain a broad knowledge of the essential concepts of big data analytics: descriptive and predictive modelling, and the construction of machine learning pipelines. The programme emphasises the importance of understanding how to build analytical solutions with production level code.

The studies in MIND are conducted in a research-oriented environment. Our researchers cover a wide range of interests in analytics and machine learning applications that you as a student or employer can benefit from, when pursuing your own domain applications. These include computer vision, machine learning operations (MLOps), trustworthy artificial intelligence (AI), interaction-based learning, text analytics, Internet of Things, robotics, physics and chemistry applications, and financial engineering.

This programme is intended for people with experience in programming and software development, and two years of relevant working experience. MIND involves a complete method renewal in companies – to learn how to make practical use of machine learning. As a student you will gain new insights, even after years of working. If you are curious about and comfortable with solving data-related problems by applying logical and mathematically inspired methods, then this programme is for you.

During the academic year 2023–2024 lectures are held on Thursdays and Fridays every second week between 13:00 and 18:00. Changes may occur for the following academic year.

What you will learn

  • Programming for analytical services
  • Data analytics
  • Machine learning
  • Data engineering
  • Data visualisation
  • Descriptive data mining
  • Predictive forecasting
  • Decision automation
  • Data science and validation of model results
  • Planning and development of analytical solutions
  • Analytics value creation

Examples of future positions

Graduates will be able to work with a wide range of tasks in various industries. Positions include development, research, analysis, and managerial positions, e.g.:

  • Big Data Analytics Developer
  • Big Data Analytics Manager
  • Data Engineer
  • Machine Learning Engineer
  • Data Scientist
  • Principal/Senior Software Developer
  • Head of Analytics
  • Chief Technology Officer (CTO)
  • Senior Analyst
  • Consultant

Take on real-world challenges

As a student, you will be involved in projects connected to real-world problems that include elements of both group work and individual achievements. The focus on actual challenges emphasises disruptive problem-solving through analytics service development. Communication and business know-how are emphasised through visual storytelling and value creation.

Specialise according to your own interests

The master’s thesis project (30 ECTS) consists of a development or research project for a client (e.g. your employer) or a collaboration with Arcada’s researchers, followed by a thesis report. You start working towards your thesis project immediately and get to show your capability of systematically performing a project with a practically applied problem as a starting point. Based on the development needs of the client/researcher, you then develop the thesis project in close co-operation with your supervisor and contact person at the commissioning company.

Tuition fees and scholarships

Please note that applicants from countries outside the European Union/EEA are required to pay tuition fees. No scholarships are available for master's degree studies, but we do have an early bird offer. Learn more on our Application pages.