Arcada

Master in Machine Intelligence and Data Science

Arcada's master's degree programme Machine Intelligence and Data Science (MIND) develops your ability to turn data into insight and deploy working systems. You will build a solid grounding in machine learning and data engineering, covering descriptive and predictive modelling, feature engineering, and the design, testing, and deployment of robust ML pipelines. We emphasise writing maintainable code and delivering usable solutions.

MIND is designed for applicants with hands-on programming experience and at least two years of relevant work. If you enjoy solving data-driven problems with modern methods, this programme will deepen your skills and prepare you to lead data-driven work in your organisation.

What you will learn

As a MIND student, you follow a one-year, full-time academic roadmap built from two parts:

1. six sequential 5 ECTS core modules covering the basics of ML, data mining, visualisation, deep learning/foundation models, cloud/data engineering, and AI-assisted service design
2. a simultaneous, year-long Research Seminar integrated with your master’s thesis. Courses are delivered in intensive blocks that typically fit six biweekly sessions, so you can focus deeply on one module at a time while progressing your thesis.

During your studies you will:

• frame problems and success metrics, then build end-to-end pipelines from ingestion and feature work to deployment
• apply supervised/unsupervised methods, data mining and forecasting, and validate results with sound experiment design and error analysis
• visualise and narrate findings for decision-making and BI
• use deep learning and foundation-model techniques where appropriate and leverage cloud/big-data tooling for scale
• design AI-assisted analytical services, from requirements to a deployable prototype.

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

Do you have a dataset or problem from your workplace or research group? You may use it in selected courses, projects, and your master’s thesis (subject to feasibility and data-governance review). We support NDAs, anonymisation, and ethical approvals where applicable. Typical outcomes include a reproducible pipeline, an evaluation report, and a deployment-ready prototype. If you are facing big-data challenges, MIND helps you scope, model, and operationalise solutions. You will learn practical methods for data engineering, scalable ML, experimental design, and performance/cost trade-offs. We can’t promise to solve your project during the degree, but you will gain the skills, patterns, and tooling to do so plus a thesis aligned with your domain.

How to apply

Please visit the Application pages for all the information on how to apply.

Cost of studies

Please note that applicants from countries outside the EU/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.

Laptop requirement

All students enrolled in the programme are expected to have a laptop they can use in their studies.