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The courses of the programme will provide a solid foundation in machine learning, statistics and optimization, with an in-depth understanding of the mathematical modelling techniques used for extracting information from large sets of complex data, and with the computational skills and algorithms for working with such data. You will also gain familiarity with a range of common problems within Data science and AI which can be solved with such techniques.
The first year includes four compulsory courses: an introduction to Data science and AI, Nonlinear optimization, Stochastic processes and Bayesian statistics, Applied machine learning, and Design of AI systems. This will give you an introduction and a good foundation for the field. The purely mathematical courses in statistics and optimization are important for data science and AI in several ways and form the mathematical foundations of machine learning. The applied courses will give you a good combination of applied theory and hands-on experiences. The courses will also include considerations of ethical, social and environmental issues.
The only compulsory element in the second year is the Master’s thesis. In addition, you will need to choose a number of compulsory elective courses and you can further choose from a wide range of elective courses. At the end of the programme, you will complete a 30 credit Master’s thesis project, where the acquired knowledge and skills are put into practice.
Through a combination of theory and practice in the courses of the program, you will gain an understanding of how and why certain models and algorithms work and will be able to identify their possibilities and limitations. You will be able to approach a real-world problem in a specific problem domain, combining existing and new methods to create an efficient solution. You will be able to continuously learn in these rapidly evolving fields, communicate with experts and non-experts in specific problem domains and to responsibly apply these technologies. You will also gain the insights to be able to understand and influence the roles of Data Science and AI in society.
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The courses of the programme will provide a solid foundation in machine learning, statistics and optimization, with an in-depth understanding of the mathematical modelling techniques used for extracting information from large sets of complex data, and with the computational skills and algorithms for working with such data. You will also gain familiarity with a range of common problems within Data science and AI which can be solved with such techniques.
The first year includes four compulsory courses: an introduction to Data science and AI, Nonlinear optimization, Stochastic processes and Bayesian statistics, Applied machine learning, and Design of AI systems. This will give you an introduction and a good foundation for the field. The purely mathematical courses in statistics and optimization are important for data science and AI in several ways and form the mathematical foundations of machine learning. The applied courses will give you a good combination of applied theory and hands-on experiences. The courses will also include considerations of ethical, social and environmental issues.
The only compulsory element in the second year is the Master’s thesis. In addition, you will need to choose a number of compulsory elective courses and you can further choose from a wide range of elective courses. At the end of the programme, you will complete a 30 credit Master’s thesis project, where the acquired knowledge and skills are put into practice.
Through a combination of theory and practice in the courses of the program, you will gain an understanding of how and why certain models and algorithms work and will be able to identify their possibilities and limitations. You will be able to approach a real-world problem in a specific problem domain, combining existing and new methods to create an efficient solution. You will be able to continuously learn in these rapidly evolving fields, communicate with experts and non-experts in specific problem domains and to responsibly apply these technologies. You will also gain the insights to be able to understand and influence the roles of Data Science and AI in society.
Admission Requirements
62+
6.5+
90+
180+
Bachelor's degree with a Major in: Engineering, Technology, Science or Mathematics
Prerequisites: Mathematics (at least 30cr., including Multivariable analysis, Linear algebra, and Mathematical statistics), Programming in a General-purpose language (e.g. C/C++/Java/Haskell or similar (at least 7,5 cr.)), and Algorithms and/or Data structures (at least 7,5 cr.)
2 Years
Sep
International
160,000 SEK
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
Data Science and AI, MSc
Campus Johanneberg, Gothenburg, Sweden
24 monthsProgramme duration
160,000 SEKTuition Fee/year
Data Science and Artificial IntelligenceMain Subject Area
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The courses of the programme will provide a solid foundation in machine learning, statistics and optimization, with an in-depth understanding of the mathematical modelling techniques used for extracting information from large sets of complex data, and with the computational skills and algorithms for working with such data. You will also gain familiarity with a range of common problems within Data science and AI which can be solved with such techniques.
The first year includes four compulsory courses: an introduction to Data science and AI, Nonlinear optimization, Stochastic processes and Bayesian statistics, Applied machine learning, and Design of AI systems. This will give you an introduction and a good foundation for the field. The purely mathematical courses in statistics and optimization are important for data science and AI in several ways and form the mathematical foundations of machine learning. The applied courses will give you a good combination of applied theory and hands-on experiences. The courses will also include considerations of ethical, social and environmental issues.
The only compulsory element in the second year is the Master’s thesis. In addition, you will need to choose a number of compulsory elective courses and you can further choose from a wide range of elective courses. At the end of the programme, you will complete a 30 credit Master’s thesis project, where the acquired knowledge and skills are put into practice.
Through a combination of theory and practice in the courses of the program, you will gain an understanding of how and why certain models and algorithms work and will be able to identify their possibilities and limitations. You will be able to approach a real-world problem in a specific problem domain, combining existing and new methods to create an efficient solution. You will be able to continuously learn in these rapidly evolving fields, communicate with experts and non-experts in specific problem domains and to responsibly apply these technologies. You will also gain the insights to be able to understand and influence the roles of Data Science and AI in society.
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The courses of the programme will provide a solid foundation in machine learning, statistics and optimization, with an in-depth understanding of the mathematical modelling techniques used for extracting information from large sets of complex data, and with the computational skills and algorithms for working with such data. You will also gain familiarity with a range of common problems within Data science and AI which can be solved with such techniques.
The first year includes four compulsory courses: an introduction to Data science and AI, Nonlinear optimization, Stochastic processes and Bayesian statistics, Applied machine learning, and Design of AI systems. This will give you an introduction and a good foundation for the field. The purely mathematical courses in statistics and optimization are important for data science and AI in several ways and form the mathematical foundations of machine learning. The applied courses will give you a good combination of applied theory and hands-on experiences. The courses will also include considerations of ethical, social and environmental issues.
The only compulsory element in the second year is the Master’s thesis. In addition, you will need to choose a number of compulsory elective courses and you can further choose from a wide range of elective courses. At the end of the programme, you will complete a 30 credit Master’s thesis project, where the acquired knowledge and skills are put into practice.
Through a combination of theory and practice in the courses of the program, you will gain an understanding of how and why certain models and algorithms work and will be able to identify their possibilities and limitations. You will be able to approach a real-world problem in a specific problem domain, combining existing and new methods to create an efficient solution. You will be able to continuously learn in these rapidly evolving fields, communicate with experts and non-experts in specific problem domains and to responsibly apply these technologies. You will also gain the insights to be able to understand and influence the roles of Data Science and AI in society.
Admission Requirements
International
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
How to get a full scholarship
Looking for a fully-funded scholarship to see you into university? Find out how to boost your chances of getting one.
Scholarships to study abroad
Find scholarships to study abroad with our lists of international scholarships – categorized by country, by subject, and by type of student.
Scholarship Applications: Frequently Asked Questions
Get answers to all your questions about scholarship applications, including tips on how to find scholarships and chances of success.
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