Key information
Duration
Start dates & application deadlines
You can apply for and start this programme anytime.
Prospective doctoral students apply for vacancies.
Language
English
- TOEFL iBT: 90
- PTE Academic: 62
- IELTS: 6.5
Credits
240 ECTS
Delivered
On Campus
Campus Location
Disciplines
Machine Learning
Overview
This Machine Learning programme offered by Uppsala University focuses on the development of computational methods that learn from data to perform tasks such as prediction, pattern recognition, and decision-making. It supports research built on core components including large datasets, mathematical models, statistical methods, and learning algorithms.
Key Facts
The academic environment combines theoretical foundations with applied research. Training enables the ability to design machine learning models, analyse data, develop algorithms, and apply these methods across different domains, while conducting independent research and communicating results effectively.
Programme Structure
Courses include:
- Data Analysis and Big Data
- Machine Learning Models
- Learning Algorithms
- Decision-making Algorithms
- Mathematical Modelling
- Statistics
- Probabilistic Methods
Admission requirements
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
- TOEFL iBT: 90
- PTE Academic: 62
- IELTS: 6.5
Other requirements
General requirements
A person meets the general entry requirements for PhD Programmes if he or she:
- has been awarded a second-cycle qualification;
- has satisfied the requirements for courses comprising at least 240 credits, of which at least 60 credits were awarded in the second-cycle; or
- has acquired substantially equivalent knowledge in some other way in Sweden or abroad.
Tuition Fees
- International: Free
- EU/EEA: Free
Additional Details
PhD programmes are free of charge in Sweden, regardless of citizenship.
