Course and Teaching Information 2025-2026

Year 1, Period 1

• Introduction to Data Science
• Data Science Study Skills (continues in Period 2)
• Academic Writing I (continues in Period 2)
• Statistics for Data Science
• 0-1 course from List A of specialisation courses

Year 1, Period 2

• Engineering of Machine Learning Systems
• Introduction to Machine Learning
• Data Science Study Skills (continues from Period 1)
• Academic Writing I (continues from Period 1)
• 0-1 course from List B of specialisation courses

Year 1, Period 3

• Data Science Project (continues in Period 4)
• Data Science Seminar (continues in Period 4)
• 2 courses from List C of specialisation courses

Year 1, Period 4

• Data Science Project (continues from Period 3)
• Data Science Seminar (continues from Period 3)
• 2 courses from List D of specialisation courses

In­tens­ive period and sum­mer courses

• After Period 4, in May, intensive courses and pop up courses are offered on varying topics
• An internship can be carried out in the summer, counting towards the degree
• Helsinki Summer School and the Open University also offer some courses during summer

Year 2, Period 1

• MSc Thesis (5 out of 30 cr)
• 2-3 courses from List A of specialisation courses OR optional studies

Year 2, Period 2

• MSc Thesis (5 out of 30 cr; continues)
• 2-3 courses from List B of specialisation courses OR optional studies

Year 2, Period 3

• MSc Thesis (10 out of 30 cr; continues)
• 1 course from List C of specialisation courses OR optional studies

Year 2, Period 4

• MSc Thesis (10 out of 30 cr; continues)
• 1 course from List D of specialisation courses OR optional studies

• Big Data Platforms
• Cognition and Brain Function (continues in Period 2; recommended for Year 2)
• Computational Statistics (recommended for Year 2)
• Computer Vision (recommended for Year 2)
• Inverse Problems 1: Convolution and Deconvolution (recommended for Year 2)
• Models and Algorithms in NLP Applications (recommended for Year 2)
• Software Architectures (recommended for Year 2)
• 2nd Data Science Seminar (available in Year 2)

• Bayesian Data Analysis
• Cognition and Brain Function (continues from Period 1; recommended for Year 2)
• Distributed Systems (recommended for Year 2)
• Human Computer Interaction (recommended for Year 2)
• Machine Translation (recommended for Year 2)
• Trustworthy Machine Learning (recommended for Year 2)
• 2nd Data Science Seminar (continued, Year 2)

• Computational Methods I
• Information Retrieval
• Network Analysis
• Philosophy of Artificial Intelligence
• Probabilistic Cognitive Modelling
• Sustainability in Computer and Data Sciences I (2 cr)
• Sustainability in Computer and Data Sciences II (3 cr)

• Advanced Bayesian Inference
• Advanced Course in Machine Learning
• Data Warehousing and Business Intelligence (*)
• Interactive Data Visualization
• Neural Networks and Deep Learning

(*) Given every other academic year (lectured in 2026)

• Cognitive Modelling Concepts (probably offered in Periods 1-2)
• High-dimensional Statistics (probably offered in Period 3)
• Programming Parallel Computers (MOOC)

As Data Science seminars you can take any of the seminars offered by the Master's Programme in Data Science or some of the seminars offered by the Master's Programme in Computer Science.

Seminars of the Master's Programme in Data Science, Autumn 2025

• Seminar: Deep Learning method for Scientific Applications
• Seminar on Algorithms for Diversification

Seminars of the Master's Programme in Computer Science, Autumn 2025

• Seminar on Big Data Management
• Seminar on Advanced Topics in Human Computer Interaction

Seminars of the Master's Programme in Life Science Informatics, Autumn 2025

• Seminar on Life Science Informatics

As Data Science seminars you can take any of the seminars offered by the Master's Programme in Data Science or some of the seminars offered by the Master's Programme in Computer Science.

Seminars of the Master's Programme in Data Science, Spring 2026

• Seminar on Multidisciplinary Viewpoints to Intelligence
• Seminar on AI Engineering

Seminars of the Master's Programme in Computer Science, Spring 2026

• Seminar on Computational Musicology
• Seminar on Data Management for Machine Learning
• Seminar on the Internet of Things