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:

Innovation development

create real innovations – products or services with social partners

Pedagogy

gain a teaching qualification by choosing additional studies in education

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:

Data Analyst

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

Software Developer

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

Artificial Intelligence Specialist

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

Admission requirements and programme structure

Cycle – first cycle

Field – applied mathematics, information systems

Form, duration – full-time studies (4 yr.)

Study type – day-time, on-campus

Location – Kaunas, Faculty of Mathematics and Natural Sciences

Language – lithuanian

Degree awarded – bachelor of mathematical sciences

Yearly price ⁱ : full-time studies – 4108 €, price per credit – 68,47 €

Financial support »

Semester

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

Electives 3 (Select 6 cr.)

Business Process Digitalization	6	On-campus learning
Business Process Management and Modernization	6	On-campus learning
Design and Analysis of Computer Algorithms	6	On-campus learning
Teamwork in Information Systems Projects	6	On-campus learning

Module name	Credits	Method of organisation

Artificial Intelligence Solutions Development	6	On-campus learning
Bayes Methods and Uncertainty Analysis	6	Blended learning
Information System Design and CASE Technology	6	On-campus learning
Stochastic Processes	6	On-campus learning

Optional Subjects 2025

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.

What will you learn

To understand the basics of multidisciplinary mathematical analysis and programming

To apply your knowledge of mathematics
To understand the principles of finance, engineering economics and multimedia

To apply the methods of mathematical analysis, algebra and probability theory
To use a foreign language in a professional environment

To apply mathematical statistics and optimisation techniques
To use database management and cryptology principles

To apply data analysis, machine learning and mathematical modelling techniques
To understand the fundamentals of information systems
To apply parallel computing techniques and perform data analysis

To carry out a product development project, testing your role as a specialist and developing your teamwork competences

To apply the principles of artificial intelligence, random processes and Bayesian methods
To examine uncertainty phenomena
To design information systems

To carry out a final project and an professional internship to consolidate mathematical competences

Admission requirements

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

Portrait photo of a young woman with long blonde hair, wearing a black blazer and a white shirt, looking directly at the camera against a light background, resting her hand gently on her chin.

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

Portrait photo of a young woman with long dark hair, wearing a white T-shirt and light blue and white striped shirt. She is looking at the camera with a calm expression. The background is neutral light grey.

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

Join an exchange programme with our international partners:

more about exchange studies

FAQ

What language is this programme taught in?

Is there a high demand for data science professionals?

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.

What will I know when I have completed this Bachelor's degree?

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.