Frequently Asked Questions

Artificial intelligence focuses on methods that enable systems to learn, perceive, reason, predict, and generate. Data engineering focuses on acquiring, organizing, processing, governing, and serving data reliably and at scale. Modern intelligent systems require both.

Yes. The program is planned as an English-medium undergraduate engineering program. Official language and preparatory-class rules are governed by university regulations.

Yes. Students may take designated courses from the Department of Computer Engineering according to the approved curriculum, prerequisites, and semester offerings.

Yes. Data Science, Machine Learning, and Deep Learning include coordinated theory and laboratory courses. Projects, internships, research activities, and application-oriented electives further support practical learning.

The compulsory curriculum establishes a common foundation. Technical electives allow students to develop depth in areas such as computer vision, natural language processing, generative AI, data engineering, robotics, health AI, and intelligent systems.

The official curriculum and ECTS Information Package should be used for credits, prerequisites, semester placement, and graduation requirements. The curriculum page on this website provides only an accessible overview.

No. AI tools are unlikely to make AI and data engineering graduates unnecessary, but they will change the work these graduates do and the skills that employers value.

Routine tasks in programming, testing, documentation, data preparation, and basic analysis will increasingly be automated. Some entry-level tasks may become less common, and producing routine code alone is likely to become less valuable. No university can guarantee what particular technologies, job titles, or labour-market conditions will look like several years from now. The more plausible outcome, however, is the transformation of technical professions rather than their disappearance.

AI tools can help people without specialist training perform certain tasks, but building dependable systems requires much more than generating code or obtaining a plausible answer. It requires the ability to define the right problem, understand mathematical and algorithmic principles, collect and manage complex data, design scalable software and data pipelines, evaluate models rigorously, and address security, privacy, fairness, ethics, and domain-specific requirements. Engineers must also determine whether an AI-generated result is correct, under what conditions it may fail, and how it can be safely integrated into a larger system.

AI and data engineers will therefore be expected to work at a higher level of abstraction. They will need to use AI tools effectively while remaining capable of questioning their outputs, detecting errors, comparing alternative approaches, and taking responsibility for the performance of complete systems. They will also design, deploy, monitor, and improve the AI technologies that others use.

Our program is designed with this changing environment in mind. It combines enduring foundations in mathematics, algorithms, computing, artificial intelligence, and data engineering with laboratory work, team projects, research experience, and the critical and responsible use of contemporary AI tools. The aim is not to train students for a fixed set of tasks, but to develop the judgment, adaptability, and capacity for continued learning needed as technologies evolve.

We cannot promise that the technologies or job titles of the future will look exactly like those of today. We can promise an education designed around foundations that endure, practical experience, intellectual curiosity, and the ability to continue learning. We are looking for students who want not only to use AI, but also to understand, question, improve, and build it.

Potential roles include AI engineer, machine-learning engineer, data engineer, data scientist, ML systems engineer, software engineer, computer vision or NLP engineer, intelligent automation engineer, research and development engineer, and related technical roles.