Data Science and Artificial Intelligence

These are times when we need people who can build systems that learn, adapt and make decisions. Here you will gain the mathematical skills needed to build complex intelligent systems and learn to critically and ethically evaluate the impact of technology. The Data Science and Artificial Intelligence study programme covers all the key areas where data science and artificial intelligence are changing the world – from cutting-edge machine learning techniques to complex data analytics.

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Programme values

KTU graduates share a joyful moment during the graduation ceremony – dressed in formal gowns, they celebrate their academic achievements. The university community honors each step taken toward professional success.

Valued by industry leaders

You will gain in-depth knowledge of cutting-edge artificial intelligence techniques and data analysis technologies, which are crucial in the fast-paced digital society.

Another angle of the “Young-Lab” auditorium shows a space where modern design, flexible layout, and functionality meet – ideal for everything from group work to creative academic projects. It reflects KTU’s commitment to delivering a holistic study experience.

Inspiring learning environment

Advanced university facilities, collaboration with AI experts and the opportunity to participate in international projects create a unique and motivating atmosphere.

Students studying using computers – a flexible academic environment that supports remote learning and self-paced study. KTU accommodates diverse learning styles.

Real-world cases

You will tackle real-world challenges in data science and artificial intelligence, using innovative tools and collaborating with business partners.

A student team collaborates on a task – part of KTU’s advanced study programs where learning happens through cooperation and solving real-world challenges.

New Freedom to shape your path

Choose specialised modules that go deeper into the topics you are most interested in, such as machine learning, neural networks or developing artificial intelligence solutions.

Career opportunities

A degree in Data Science and Artificial Intelligence opens up diverse opportunities to work with complex data analysis and develop artificial intelligence solutions. You will gain the skills to analyse data, build predictive models, and create decision-making systems across various industries, including healthcare, finance, and technology.

Here are some of the career paths you can pursue after your studies:

Data Scientist

Analyses large amounts of data using statistical and machine learning techniques to extract valuable insights.

Artificial Intelligence Engineer

Develops and deploys machine learning and IoT models that help organisations automate processes and make smart decisions.

AI Ethics Consultant

Advises companies on the responsible and ethical use of artificial intelligence and machine learning, following legal and ethical standards.

Admission requirements and programme structure

Cycle – second cycle

Field – applied mathematics

Form, duration – full-time studies (1,5 yr.)

Study type – day-time, blended learning

Location – Kaunas, Faculty of Mathematics and Natural Sciences

Language – english

Degree awarded – master of mathematical sciences

Yearly price ⁱ : full-time studies – 5538 €, price per credit – 92,3 €

Financial support »

Semester

Module name	Credits	Method of organisation

Data Science Project	6	Blended learning
Ethics of Artificial Intelligence	6	On-campus learning
Mathematical Methods of Artificial Intelligence	9	Blended learning
Statistical Data Analysis and Forecasting Methods	9	On-campus learning

Module name	Credits	Method of organisation

Advanced Mathematical Methods of Artificial Intelligence	6	Blended learning
Artificial Intelligence Application Project	6	Blended learning
Neural Networks	6	On-campus learning

Electives (Select 12 cr.)

Combinatorial Optimisation	6	Blended learning
Data-driven Decision Making	6	Blended learning
Data-driven Methods of Mathematical Modelling	6	On-campus learning

Module name	Credits	Method of organisation

On-campus learning

Good to know

Module – a part of a study programme consisting of several related topics.
Credit – a unit of the volume of a study module in hours.
On-campus – learning on the university premises.
Blended – learning on the university premises and online.

Module – a part of a study programme consisting of several related topics.
Credit – a unit of the volume of a study module in hours.
On-campus – learning on the university premises.
Blended – learning on the university premises and online.

Module – a part of a study programme consisting of several related topics.
Credit – a unit of the volume of a study module in hours.
On-campus – learning on the university premises.

Admission requirements

University bachelor degree certificate:	Bachelor’s degree in the field of mathematics OR other study fields and ≥ 30 credits of completed subjects in the study fields of mathematics.
Proficiency in English:	IELTS ≥ 6.0, TOEFL ≥ 85, CEFR ≥ C1, or previously completed studies in english language.
Transcript requirements:	Obtain a suitable transcript of your bachelor's degree from your school. If unavailable, provide official translations and verified copies of the original documents.
Accepted languages:	English / Russian
Document legalisation:	The documents must be legalised (Apostille) by the Ministry of Foreign Affairs of the country where the documents were issued. This requirement does not apply to the documents issued in the EU and Belarus, Ukraine.

Score structure

◼	0,9	average grade (CGPA) of University‘s Bachelor’s degree (min. length – 180 ECTS) and its supplement
◼	0,1	motivation letter and online interview
+	≤ 4	additional points

Additional points

science activities (scientific publications, presentations at scientific conferences, participation in exhibitions, work in student science society or science group etc.) or art activities (publication or realization of artwork, participation in art exhibitions, contests of architecture)	≤ 2
at least 1 year of work experience in the field of study programme	0,5
graduated from academic talent development program in higher education institution (for example "GIFTed talent academy")	0,5
partial studies in the higher education institution abroad with ≥24 ECTS completed	0,5
bachelor's or master's (if integrated study programme is completed) degree diploma with honours	0,5

admission procedure

Testimonials

Portrait photo of a young man with dark hair and glasses, wearing a black t-shirt-style top, looking directly at the camera against a light background.

This study programme is designed for working professionals, with lectures scheduled to fit into just two days a week. During my master’s studies, I had the opportunity to join a team at work responsible for applying machine learning techniques to key strategic projects. Without the skills I gained during my studies, taking this step in my career would have been much more challenging.

Justas Janickas

1st year student

FAQ

Is data analysis one of the possible career paths after graduation?

Yes, graduates of this programme will be well prepared for a career in data analysis. You will gain advanced skills in data modelling, statistical analysis and programming, which are essential skills for a data analyst. In addition, the programme focuses on working with large datasets, predictive modelling and data visualisation, enabling you to tackle complex real-world challenges across a range of industries.

Why should I choose to study Data Science and Artificial Intelligence at KTU?

KTU offers a cutting-edge curriculum that combines theoretical knowledge with practical applications in data science and artificial intelligence. The programme provides access to state-of-the-art laboratories, collaboration with industry leaders, and opportunities to work on real-world projects. KTU’s strong focus on interdisciplinary learning and research ensures that students are equipped to tackle the challenges of AI and data science in diverse fields such as healthcare, finance, and more.

What are the main criteria for admission to the programme?

To enrol on the Data Science and Artificial Intelligence programme, you need a Bachelor’s degree in mathematics, computer science, engineering or a related field. A strong foundation in mathematics, programming and statistics is essential. If you do not have a direct academic background in these areas, but have relevant work experience or additional study, your application may be considered on an individual basis.