Artificial Intelligence

AI solutions that change the world
This study programme prepares you to develop intelligent software systems using machine learning, image recognition and data analysis algorithms. You will develop solutions to real-world challenges in business, academia and the public sector. Artificial Intelligence graduates will be at the forefront of technological change, shaping the solutions of the future. This is your path to a world of innovation, where you can contribute to the development of advanced technologies.

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Programme values

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

Valued by industry leaders

The modules are taught by scientists – experts in their field, actively involved in international and national research and study projects. Practitioners share their knowledge and experience in guest lectures, providing valuable insights from real-life professional activities.

KTU’s Santaka Valley building – a state-of-the-art research and innovation hub where academia and business collaborate. This is where future solutions are born.

Inspiring learning environment

For computationally intensive research, you will be able to use the infrastructure provided by the University, such as the High-Performance Computing System. You will also have access to state-of-the-art independent learning and collaborative workspaces.

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

Real-world cases

Students work with social partners and experienced researchers in teams from different fields of study to develop products from conception to implementation. Case studies, simulations of real situations, inquiry-based learning and other innovative learning methods are used in the studies.

A student raises his hand during discussion – KTU encourages active participation, critical thinking, and self-driven decision-making. Flexible study paths allow each learner to shape their own academic journey.

New Freedom to shape your path

Students of this study programme can choose alternative modules according to their interests and develop a personal study path, delving deeper into their chosen field.

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

Innovation development

create real innovations – products or services with social partners

Career opportunities

Learn how to develop intelligent software systems using machine learning, image recognition and data processing and analysis algorithms.
Choose your career path in artificial intelligence, intelligent applications and information technology (IT) services. The knowledge and skills you gain will enable you to become an expert in a highly sought-after field, understanding the potential of artificial intelligence and how to apply it in IT companies, start-ups or as a freelancer.

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

Artificial Intelligence Solutions Developer

Develops and deploys applications using artificial intelligence technologies. Develops models, optimises algorithms and integrates solutions.

AI Systems Analyst

Analyses data, identifies AI trends, trains models and evaluates system performance.

Developer of Human-Assisted Intelligent Systems

Designs, develops and programs artificial intelligence systems that help people solve problems, streamline processes and improve efficiency.

Admission requirements and programme structure

Cycle – first cycle

Field – informatics

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

Study type – day-time, on-campus

Location – Kaunas,
Faculty of Informatics

Language – Lithuanian, English

Degree awarded – bachelor of computing

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

Financial support »

Semester

Module name	Credits	Method of organisation

Application of Cognitive Neuroscience	3	Blended learning
Artificial Intelligence Ecosystems	6	On-campus learning
Introduction to Object-Oriented Programming	6	On-campus learning
Introduction to Studies of Informatics	9	On-campus learning
Mathematics 1	6	On-campus learning

Module name	Credits	Method of organisation

Databases	6	On-campus learning
Mathematics 2	6	On-campus learning
Object-Oriented Programming 2	6	On-campus learning
The First Principles of Digital Logic	6	On-campus learning

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

Media Philosophy	6	Blended learning
Sustainable Development	6	Blended learning

Module name	Credits	Method of organisation

Academic and Technical Communication in English (Level C1)	6	On-campus learning
Computer Architecture	6	On-campus learning
Data Processing and Analysis	6	On-campus learning
Data Structures	6	On-campus learning
Discrete Structures	6	On-campus learning

Module name	Credits	Method of organisation

Algorithms for Big Data Processing	6	On-campus learning
Design and Analysis of Computer Algorithms	6	On-campus learning
Fundamentals of Multi-Agent Systems	6	On-campus learning
Operating Systems	6	On-campus learning
Software Engineering	6	On-campus learning

Module name	Credits	Method of organisation

Computer Networks and Internet Technologies	6	On-campus learning
Fundamentals of Information Systems	6	On-campus learning
Image Processing Algorithms	6	On-campus learning
Machine Learning Algorithms 1	6	On-campus learning
Numerical Methods and Algorithms	6	Blended learning

Module name	Credits	Method of organisation

Deep Learning	6	On-campus learning
Machine Learning Algorithms 2	6	On-campus learning
Product Development Project	12	On-campus learning
System Simulation	6	On-campus learning

Module name	Credits	Method of organisation

Cloud Computing for Artificial Intelligence	6	On-campus learning
Speech Recognition Algorithms	6	On-campus learning

Optional Subjects 2025

Electives 1 (Select 6 cr.)

Artificial Intelligence for Gaming	6	On-campus learning
Intelligent Assistive Systems Technologies	6	On-campus learning
Robot Programming Technologies	6	On-campus learning

Electives 2 (Select 6 cr.)

Artificial Intelligence in Business Processes	6	Blended learning
Business Ethics	6	On-campus learning

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.
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.

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.
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.

Admissions requirements

Proficiency in English	IELTS ≥ 5.5, TOEFL ≥ 75, CEFR ≥ B2, or equivalent.
Eligibility criteria:	High school certificate.Maximum 3 years after high school graduation. Minimum average grade (CGPA) >60% in each entry subject.
Transcript requirements:	Obtain a suitable transcript from your school. If unavailable, provide official translations and verified copies of the original documents.
Accepted languages:	English / Russian.
Document legislation:	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 EU and Belarus, Ukraine documents.

Score structure

◼	0,5	entry exam	mathematics
◼	0,3	final exam	information technologies or physics, or biology, or chemistry, or geography
◼	0,2	final exam	English language

admission procedure preparatory courses

Testimonials

Artificial intelligence covers many disciplines, from computer vision to natural language processing, and has a wide range of applications, from medicine to manufacturing and transport. I started my career while still studying at the university, and am currently working in reproductive medicine field, on a project that uses the latest technology to predict the receptive phase of the endometrium, which is important for determining the exact window for implantation.

Marius Vainauskis

3rd year student

Portrait photo of a young man with long curly hair and a beard, wearing a black sweater. He is looking at the camera with a slight smile. The background is neutral light grey.

When I started studying Artificial Intelligence at KTU, I realised that studies can be informative, interactive and even fun. The most important thing is to choose studies that really match your interests and hobbies. During the lectures, we created an interactive model to play the game Connect 4, and in the end, all the models played against each other. It was interesting to see the solutions and strategies chosen by colleagues.

Vilius Bankauskas

KTU alumnus, Light Technologies Assistant, TMT

Portrait photo of a young woman with short curly hair, wearing a checkered blazer and a black top. She is wearing round glasses with thin frames and smiling while looking at the camera. The background is neutral light grey.

The field of Artificial Intelligence (AI) is currently experiencing rapid growth and the need for professionals is increasing worldwide. KTU graduates enter the job market with a strong technological foundation and the ability to develop business-relevant IoT solutions. The strength of these professionals lies not only in their theoretical knowledge but also in the practical experience gained during their studies, which allows them to easily integrate into the working environment and quickly solve complex problems.

Monika Pavalkytė

Education Project Manager, Cognizant

International mobility partners

Join an exchange programme with our international partners:

more about exchange studies

FAQ

What type of companies employ AI specialists?

AI specialists are employed by various companies that use or develop intelligent systems or AI-based automation solutions in image analysis, natural language processing, process optimisation and other areas.

How quickly can students start a career in AI?

Typically, Artificial Intelligence students begin work during their final year of study or professional internship.

What equipment do I need for these studies?

For studies, a standard computer is sufficient to prepare written work, watch video lectures and participate in remote consultations and discussions. There is no need for specialised equipment; if necessary, remote computing resources provided by the University can be used for computationally demanding tasks.

Why should I choose to study AI at KTU?

Studying AI at KTU is a great choice if you’re looking to build a strong foundation for a career in the tech world. The courses are well-structured, so you’ll gain all the essential skills you need to succeed as an AI specialist and IT professional. Beyond the classroom, KTU offers state-of-the-art facilities for developing real-world AI solutions. You’ll also have countless opportunities to connect with passionate lecturers, like-minded classmates and supportive industry partners who can help you make the most of your time here.