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Artificial Intelligence in Computer Science

Artificial Intelligence in Computer Science is transforming society and tackling global challenges through technological innovation. This programme trains experts to develop advanced informatics models for computer vision, speech recognition, semantic analysis and data generation solutions. You will gain knowledge of state-of-the-art methods in deep learning, optimisation and data analysis, enabling you to conduct independent research, develop innovative systems and lead the development of IT projects.

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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

The modules are taught by researchers – specialists in their field, actively involved in international and national research and study projects. 

Guest lectures by practitioners sharing their knowledge and experience are delivered throughout the studies. 

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

For computationally intensive research, will allow you to use the infrastructure provided by the University, such as the High-Performance Computing (HPC) system. You can also use modern spaces for independent and collaborative learning. 

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

Students carry out applied research in computer science and artificial intelligence in collaboration with business partners or public sector organisations. The modules use real-life case studies, simulation and challenge-based learning. 

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

Students can specialise in a narrower field of study gaining expertise in their chosen field. The MA+ option allows you to broaden your knowledge and acquire cross-disciplinary expertise in a complementary field, such as data analytics, data security or project management, in addition to your main field. 

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

Interdisciplinary competence
select a set of study modules from a different field to your main studies

Career opportunities

The programme provides in-depth knowledge of image processing, generative intelligence and the development of artificial intelligence models. During your studies, you will acquire key skills in information technology (IT) project management and the design of computer models based on artificial intelligence methods.
You’ll be able to start your career as a scientist – solving scientific challenges in IT systems, planning, performing and analysing computational experiments and calculations.

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

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

Designs, implements and develops systems integrating artificial intelligence technologies.

Icon of a digital analytics dashboard – represents career paths in data analysis, business intelligence, and performance tracking using modern tech tools.
Artificial Intelligence Specialist

Develops, refines and applies AI algorithms and models to enable systems to perform tasks that would normally require human intelligence.

Monitor showing a system path diagram – reflects digitalisation of complex systems, strategic planning, and digital transformation.
Developer of Autonomous Systems (machines, drones, etc.)

Designs, programs and tests autonomous systems, such as machines or drones, to ensure their autonomous operation, navigation and decision-making in different contexts.

Admission requirements and programme structure

An arrow icon pointing right – represents the study level (Bachelor, Master, or PhD) in a structured academic path.
Cycle – second cycle
A document icon refers to the field of study – such as engineering, technology, business, and more.
Field – informatics
A clock icon indicates the form and duration of the programme.
Form, duration – full-time studies (2 yr.)
A calendar icon indicates the mode of study – full-time, remote, or blended learning.
Study type – evening-time, blended learning
A location pin icon marks the place where the study programme is delivered – within a top-rated university in Lithuania.
Location – Kaunas, Faculty of Informatics
A speech bubble icon represents the language of instruction – often English for international, top-rated study programmes.
Language – english, 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 – master of computing
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 – 5538 €, price per credit – 92,3 €

Semester

Module name Credits Method of organisation
Computational Intelligence and Decision Making 6 Blended learning
Distributed Systems and Algorithms 6 Blended learning
Image Processing and Computer Vision 6 Blended learning
Research Project 1 6 Blended learning

Competence Electives (Select 6 cr.)

Courses of Study Field (Competence of Expert) 6
Optional Competence of MA+ 6

Business Process and Supply Chain Management

Business Process Management 6 Blended learning

Challenge-Based Innovations

Development of Challenge-Based Innovation 3 Blended learning
Optional Micro-modules 3 Distance learning

Computer Visualization Technologies

Multimedia Content Creation Methods 6 Blended learning

Control Technologies

Modern Sensors and Systems 6 On-campus learning

Data Analytics

Data Mining Methods 6 Blended learning

Data Security

Cryptographic Systems 6 Blended learning

Language Studies (French)

Studies of Modern Languages (Level A1) 6 On-campus learning
Studies of Modern Languages (Level A2) 6 On-campus learning
Studies of Modern Languages (Level B1) 6 On-campus learning

Language Studies (German)

Studies of Modern Languages (Level A1) 6 On-campus learning
Studies of Modern Languages (Level A2) 6 On-campus learning
Studies of Modern Languages (Level B1) 6 On-campus learning

Language Studies (Italian)

Studies of Modern Languages (Level A1) 6 On-campus learning
Studies of Modern Languages (Level A2) 6 On-campus learning
Studies of Modern Languages (Level B1) 6 On-campus learning

Language Studies (Russian)

Studies of Modern Languages (Level A1) 6 On-campus learning
Studies of Modern Languages (Level A2) 6 On-campus learning
Studies of Modern Languages (Level B1) 6 On-campus learning

Language Studies (Spanish)

Studies of Modern Languages (Level A1) 6 On-campus learning
Studies of Modern Languages (Level A2) 6 On-campus learning
Studies of Modern Languages (Level B1) 6 On-campus learning

Language Studies (Swedish)

Studies of Modern Languages (Level A1) 6 On-campus learning
Studies of Modern Languages (Level A2) 6 On-campus learning
Studies of Modern Languages (Level B1) 6 On-campus learning

Legal Awareness

Business Law 6 Blended learning

Management

Strategic Management 6 On-campus learning

Project Management

Project Planning and Organisation 6 Blended learning

Public Communication

Studies of Modern Languages (Level C1) 6 On-campus learning

Regulation and Evaluation of Business Markets

Business Regulation 6 Blended learning
Module name Credits Method of organisation
Explainable Artificial Intelligence 6 On-campus learning
Generative Artificial Intelligence 6 Blended learning
Optimisation Techniques and Algorithms 6 Distance learning
Research Project 2 6 Blended learning

Competence Electives (Select 6 cr.)

Courses of Study Field (Competence of Expert) 6
Optional Competence of MA+ 6

Business Process and Supply Chain Management

Quality Management 6 Distance learning

Challenge-Based Innovations

Development of Challenge-Based Innovation 6 Distance learning

Computer Visualization Technologies

Principles of Image Perception 6 Blended learning

Control Technologies

Application of Artificial Intelligence in Robotics and their Systems Control 6 Blended learning

Data Analytics

Multivariate Statistical Models 6 Blended learning

Data Security

Data Security Technologies 6 Blended learning

Language Studies (French)

Studies of Modern Languages (Level A2) 6 On-campus learning
Studies of Modern Languages (Level B1) 6 On-campus learning
Studies of Modern Languages (Level B2) 6 On-campus learning

Language Studies (German)

Studies of Modern Languages (Level A2) 6 On-campus learning
Studies of Modern Languages (Level B1) 6 On-campus learning
Studies of Modern Languages (Level B2) 6 On-campus learning

Language Studies (Italian)

Studies of Modern Languages (Level A2) 6 On-campus learning
Studies of Modern Languages (Level B1) 6 On-campus learning
Studies of Modern Languages (Level B2) 6 On-campus learning

Language Studies (Russian)

Studies of Modern Languages (Level A2) 6 On-campus learning
Studies of Modern Languages (Level B1) 6 On-campus learning
Studies of Modern Languages (Level B2) 6 On-campus learning

Language Studies (Spanish)

Studies of Modern Languages (Level A2) 6 On-campus learning
Studies of Modern Languages (Level B1) 6 On-campus learning
Studies of Modern Languages (Level B2) 6 On-campus learning

Language Studies (Swedish)

Studies of Modern Languages (Level A2) 6 On-campus learning
Studies of Modern Languages (Level B1) 6 On-campus learning
Studies of Modern Languages (Level B2) 6 On-campus learning

Legal Awareness

Administrative Law 6 Blended learning

Management

Management of Persons and their Groups 6 On-campus learning

Project Management

Project Social and Economical Evaluation 6 Blended learning

Public Communication

Academic Writing 6 On-campus learning

Regulation and Evaluation of Business Markets

Industrial economics 6 On-campus learning
Module name Credits Method of organisation
Information Technology Project Management 6 Blended learning
Research Project 3 6 Blended learning

Electives of Applied Research (Select 12 cr.)

Applied Research Project 12 Blended learning
Scientific Internship 12 Blended learning

Competence Electives (Select 6 cr.)

Courses of Study Field (Competence of Expert) 6
Optional Competence of MA+ 6

Business Process and Supply Chain Management

Business Process Analytics 6 Blended learning

Challenge-Based Innovations

Optional Challenges 6 Distance learning

Computer Visualization Technologies

3D Visualization Methods 6 Blended learning

Control Technologies

Programmable Logical Controllers 6 Blended learning

Data Analytics

Time Series Analysis 6 Blended learning

Data Security

Blockchain Methods 6 On-campus learning

Language Studies (French)

Studies of Modern Languages (Level B1) 6 On-campus learning
Studies of Modern Languages (Level B2) 6 On-campus learning
Studies of Modern Languages (Level C1) 6 On-campus learning

Language Studies (German)

Studies of Modern Languages (Level B1) 6 On-campus learning
Studies of Modern Languages (Level B2) 6 On-campus learning
Studies of Modern Languages (Level C1) 6 On-campus learning

Language Studies (Italian)

Studies of Modern Languages (Level B1) 6 On-campus learning
Studies of Modern Languages (Level B2) 6 On-campus learning
Studies of Modern Languages (Level C1) 6 On-campus learning

Language Studies (Russian)

Studies of Modern Languages (Level B1) 6 On-campus learning
Studies of Modern Languages (Level B2) 6 On-campus learning
Studies of Modern Languages (Level C1) 6 On-campus learning

Language Studies (Spanish)

Studies of Modern Languages (Level B1) 6 On-campus learning
Studies of Modern Languages (Level B2) 6 On-campus learning
Studies of Modern Languages (Level C1) 6 On-campus learning

Language Studies (Swedish)

Studies of Modern Languages (Level B1) 6 On-campus learning
Studies of Modern Languages (Level B2) 6 On-campus learning
Studies of Modern Languages (Level C1) 6 On-campus learning

Legal Awareness

Labour Law 6 Blended learning

Management

Business Process Management 6 Blended learning
Financial Management Decisions 6 Blended learning
Legal Regulation of Management Activities 6 Blended learning
Marketing Management 6 Blended learning
Negotiation and Conflict Management 6 Blended learning
Project Planning and Organisation 6 Blended learning
Psychology of Leadership and Management 6 Blended learning

Project Management

Project Quality and Risk Management 6 Blended learning

Public Communication

Public Speaking 6 On-campus learning

Regulation and Evaluation of Business Markets

Economical Valuation of Innovations 6 Blended learning
Module name Credits Method of organisation
Master’s Degree Final Project 30 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.
  • Distance – almost all learning 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.
  • Distance – almost all learning 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.
  • Distance – almost all learning 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 discover and apply artificial intelligence and machine learning
  • To implement distributed systems
  • To apply image analysis techniques
  • To develop models of explanatory and generative AI
  • To apply optimisation techniques and algorithms
  • To develop and manage an IT project
  • To undertake research projects
  • To analyse the results of the study
  • To implement solutions related to artificial intelligence

Admission requirements

University bachelor degree certificate: Engineering sciences, technologies, mathematical sciences, computer sciences and physical sciences and ≥ 30 credits of completed subjects in the study fields of informatics, informatics engineering or 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
admission procedure

Testimonials

A short-haired man wearing glasses and a black suit, standing with arms crossed against a light background.

We study specific branches of Artificial Intelligence (AI), giving you a better understanding of the different tools available in AI. This leads to better prospects in the job market. This master’s programme also offers flexible learning opportunities with MA+. This allows you to personalise your studies more and to choose a set of modules that are aligned with your career goals.

Modestas Butnorius
1st year student
Portrait photo of a young man with short brown hair, wearing glasses, a grayish-blue hoodie, and a dark T-shirt underneath. He is looking at the camera with arms crossed against a neutral gray background.

I chose to study for a master’s to further my knowledge, and in this programme, I found most of the modules I was interested in related to machine learning, video, audio and other signal processing. My studies have given me more opportunities to work on complex tasks, and the knowledge and practical skills I have acquired during my studies have helped me to better understand complex algorithms and their applications in real-life situations.

Marius Teleiša
KTU alumnus, Mid Test Automation Engineer, Teltonika Networks
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.

KTU graduates enter the job market with not only a strong understanding of artificial intelligence (AI) but also the ability to apply it in real-world scenarios. Master’s studies offer the opportunity to deepen theoretical knowledge while gaining practical experience in applying the latest Internet of Things (IoT) methodologies and models – tools that have a direct impact on both business and society. As companies seek greater efficiency, reduced costs, and improved results, IoT professionals are becoming increasingly indispensable.

Monika Pavalkytė
Education Project Manager, Cognizant

International mobility partners

Join an exchange programme with our international partners:
more about exchange studies
more about exchange studies

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FAQ

Studying the Artificial Intelligence in Computer Science programme opens up a wide range of career opportunities. AI is transforming industries such as healthcare, finance and technology, creating high-paying jobs in machine learning, data science and automation. It’s an innovative field with global demand, offering research opportunities and even pathways to entrepreneurship. AI skills are interdisciplinary, combining programming, maths and problem solving. With AI shaping the future, graduates gain versatile, future-proof expertise that opens doors to exciting and impactful careers worldwide.

Is it possible to combine working and studying?

Yes, because lectures in the Artificial Intelligence in Computer Science programme take place in the evening, usually from 17:30 to 21:00. Most lectures are organised as distance learning, making it an ideal option for those who want to combine their studies with work or other activities.

 

Contacts

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

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

let's talk

Faculty of Informatics
XI Chamber
Studentų St. 50, LT-51368 Kaunas
email if@ktu.lt

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