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Data Science and Engineering

The power of data at your fingertips
We live in a world where every piece of data can have enormous value. This programme combines data science and engineering, giving you the opportunity to learn how to analyse, process and apply data to a wide range of problems. You’ll gain a background in data analysis and learn how to use cutting-edge tools to build artificial intelligence systems and predict market trends. Graduating from this programme will open up many opportunities to work with data analytics and there is a huge demand for these professionals today.

in Lithuanian

Programme values

A lecturer leads a session in the modern “Young-Lab” classroom, combining technology and a creative atmosphere. It’s a space where inspiring discussions and new ideas come to life.
Valued by industry leaders

You will gain knowledge in data analysis, engineering and artificial intelligence, which is highly valued in international technology companies and academia. 

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

Contemporary laboratories, international opportunities and a dynamic community provide inspiration and support to achieve ambitious personal and professional goals. 

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

Hands-on projects and collaboration with companies will allow you to develop innovative solutions and gain the unique experience needed in the data ecosystem today. 

Talented students from different fields gather for shared activities – proof that KTU’s community is creative, ambitious, and growth-driven.
New Freedom to shape your path

You can choose specialised modules to develop specific skills and focus on areas of data science and engineering that interest you. 

In this study programme, you can choose the following study paths:

Career opportunities

A Bachelor’s degree in Data Science and Engineering opens up a wide range of career opportunities working with big data, analysing it and developing solutions based on the insights it provides. You’ll be able to contribute to technological advances in sectors as diverse as finance, healthcare and industry.

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

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Data Analyst

Collects, processes and analyses data to discover relevant business insights and make informed decisions.

Bracketed code icon – showcasing abilities and skills in IT, coding, programming, backend development, software engineering and working with AI (artificial intelligence) systems.
Software Developer

Designs and develops systems that process and analyse data and ensure their efficiency and performance.

A user profile icon connected to a digital interface – represents career opportunities in digital identity management, tech consultancy, media specialization, and roles as a technology specialist after graduating from a top-rated study programme.
Artificial Intelligence Specialist

Develops and applies algorithms to automate processes and improve decision-making systems in various industries.

Admission requirements and programme structure

An arrow icon pointing right – represents the study level (Bachelor, Master, or PhD) in a structured academic path.
Cyclefirst cycle
A document icon refers to the field of study – such as engineering, technology, business, and more.
Field – applied mathematics, information systems
A clock icon indicates the form and duration of the programme.
Form, duration full-time studies (4 yr.)
A calendar icon indicates the mode of study – full-time, remote, or blended learning.
Study typeday-time, on-campus
A speech bubble icon represents the language of instruction – often English for international, top-rated study programmes.
Language – lithuanian
A graduation cap icon represents the degree awarded upon completion – bachelor’s, master’s, or doctoral qualification from a top university in Lithuania.
Degree awarded – bachelor of mathematical sciences
An icon with the euro symbol shows the annual tuition fee – clearly presenting the cost of investing in quality education.
Yearly price i : full-time studies – 4108 €, price per credit – 68,47 €
Module name Credits Method of organisation
Discrete Mathematics 6 On-campus learning
Geometry 6 On-campus learning
Introduction to Mathematics and Informatics Studies 6 On-campus learning
Introduction to Object-Oriented Programming 6 On-campus learning
Mathematical Analysis 1 6 On-campus learning
Module name Credits Method of organisation
Linear Algebra 6 On-campus learning
Mathematical Analysis 2 6 On-campus learning
Programming for Data Processing and Visualization 6 On-campus learning

Electives of Philosophy and Sustainable Development 2025 (Select 6 cr.)

Media Philosophy 6 Blended learning
Sustainable Development 6 Blended learning

Object Programming Electives (Select 6 cr.)

Fundamentals of Object-Oriented Programming 2 6 On-campus learning
Object-Oriented Programming 2 6 On-campus learning
Module name Credits Method of organisation
Mathematical Analysis 3 6 On-campus learning
Mathematics Software 6 On-campus learning
Physics 1 6 On-campus learning
Theory of Probability 6 On-campus learning

Foreign Language Electives (Level C1) 2025 (Select 6 cr.)

Academic and Technical Communication in English (Level C1) 6 On-campus learning
Academic and Technical Communication in French (Level C1) 6 On-campus learning
Academic and Technical Communication in German (Level C1) 6 On-campus learning
Module name Credits Method of organisation
Cryptology 6 On-campus learning
Databases 6 On-campus learning
Mathematical Statistics 6 On-campus learning
Optimization Methods 6 On-campus learning

Electives 1 (Select 6 cr.)

Business Process Digitalization 6 On-campus learning
Business Process Management and Modernization 6 On-campus learning
Teamwork in Information Systems Projects 6 On-campus learning
Module name Credits Method of organisation
Data Analysis 6 On-campus learning
Fundamentals of Information Systems 6 On-campus learning
Machine Learning Methods 6 On-campus learning
Methods of Mathematical Modelling 6 On-campus learning

Electives 2 (Select 6 cr.)

Business Intelligence and Data Mining 6 On-campus learning
Parallel Computing and Distributed Databases 6 On-campus learning
Module name Credits Method of organisation
Applied Multivariate Analysis 6 On-campus learning
Deep Learning 6 On-campus learning
Product Development Project 12 On-campus learning
Optional Subjects 2025 6
Module name Credits Method of organisation
Bachelor’s Degree Final Project 15 On-campus learning
Professional Internship 15 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.

The programme is only conducted in Lithuanian language. Entry requirements for this particular programme can be found in the programme description provided in Lithuanian language.

in Lithuanian

Testimonials

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The Data Science and Engineering programme is all about analysing data, processing it and extracting valuable insights. At KTU, I gained practical skills to work with real data and develop artificial intelligence (AI) solutions. Analytical science is usually more expensive than technical knowledge, which is why professionals in this field are in high demand today.

Meda Budrytė
4th year student
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Data science tools and techniques are versatile, so the knowledge gained can be applied to almost any field. This study programme gives you a strong start and the freedom to choose where and how you want to grow. Studying at KTU has given me a solid foundation for my current professional career. The most memorable thing was the variety of study modules and their applicability in practice. My studies in complementary pedagogy also contributed to my success.

Saulė Bielevičiūtė
1st year student

International mobility partners

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FAQ

Yes, the demand for data science professionals is growing both in Lithuania and internationally. Companies in sectors ranging from finance and healthcare to logistics and technology are actively looking for professionals who can work with big data, create predictive models and generate added value from data.

The Data Science and Engineering degree gives you the knowledge and skills to collect, analyse, process and visualise large data sets. You will learn machine learning algorithms, artificial intelligence applications, cloud computing solutions, database management, programming and data visualisation techniques and applications. You will also develop critical thinking, problem solving and project management skills.

 

Contacts

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Talk to us, study with us:
K. Donelaičio St. 73, LT-44249 Kaunas
phone: +370 679 44 555
email studijos@ktu.lt

let's talk

Faculty of Mathematics and Natural Sciences
XI Chamber
Studentų St. 50, LT-51368 Kaunas
email mgmf@ktu.lt

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Contact photo of Silvia Petniūnaitė wearing a black blazer representing KTU study info specialists consulting international students.

Student Info Center
Student Info Center
Studentų St. 50, LT-51368 Kaunas
email international@ktu.lt

let's talk

Faculty of Mathematics and Natural Sciences
XI Chamber
Studentų St. 50, LT-51368 Kaunas
email mgmf@ktu.lt

Button Iconvirtual tour