Łódź, Poland

Computer Science

Master's
Table of contents
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Computer Science at AHE Łódź

Language: EnglishStudies in English
Subject area: computer science
Kind of studies: part-time studies

Why study Computer Science?

Computer Science dlaczego II
Dlaczego warto:

Advanced learning in English

The Master’s in Computer Science at the University of Humanities and Economics in Lodz is offered at a non-public institution and taught in English. This setting builds fluent technical communication, prepares graduates for international teams and opens access to global documentation, conferences and communities. From the outset students engage with specialised terminology and defend ideas clearly during seminars, labs and project reviews.

Research-driven curriculum

Second-cycle studies deepen core computer science while opening space for exploration of emerging fields. Students analyse current approaches, compare architectures and evaluate trade-offs with an academic rigour expected at postgraduate level. Emphasis is placed on formulating research questions, selecting methods, validating results and reflecting on limitations, which strengthens the quality of the final thesis and future professional decision-making.

Industry-style projects and laboratories

Project work mirrors real delivery environments: requirement analysis, iterative design, implementation, testing and maintenance. Students practise version control, code reviews and documentation so that every assignment can evolve into a demonstrable portfolio piece. Exposure to practices such as continuous integration, containerisation or cloud deployment helps translate classroom knowledge into systems that are robust, observable and ready for production.

Specialisations that shape expertise

The programme enables targeted development in areas aligned with interests and career goals. Whether a student leans towards data engineering, artificial intelligence, cybersecurity, distributed systems or software architecture, the pathway encourages deliberate choices supported by workshops and consultations. This focus refines technical depth while maintaining a broad understanding of how components interact within modern digital ecosystems.

Mentoring, supervision and academic support

Close cooperation with supervisors helps define research scope, select tools and plan milestones. Constructive feedback improves methodology and writing, while regular consultations keep projects on track. Access to engaged academics and practitioners also facilitates networking, references and insight into current market expectations, which is particularly valuable when turning thesis topics into professional initiatives.

Leadership and communication for tech teams

Beyond advanced coding, students cultivate skills that accelerate careers: technical storytelling, stakeholder communication and responsible decision-making. Practice in presenting prototypes, running retrospectives and prioritising backlogs builds confidence in leading sprints and coordinating contributors. Attention to ethics, accessibility and data protection ensures graduates design solutions that are not only effective but also trustworthy and compliant.

Flexible organisation supports work-study balance

The structure of teaching forms—lectures, seminars and laboratories—allows steady progression without losing room for employment, internships or entrepreneurial ventures. Many tasks are project-based, so professional challenges can inform academic work and vice versa. Such flexibility helps students gather experience while studying, creating a coherent narrative for future recruiters and accelerating entry into advanced roles.

Career outcomes and academic progression

Graduates are prepared for positions requiring expert judgement and systems thinking: solution architect, data or AI specialist, security engineer, DevOps practitioner or technical lead. The programme also forms a solid foundation for doctoral studies and research careers. Studying in English eases collaboration with international teams and enables smooth participation in cross-border projects and communities.

Lodz ecosystem and networking opportunities

Lodz offers a lively environment for tech growth with meet-ups, workshops and collaborative initiatives where students can validate ideas with practitioners. Engagement in local projects, hackathons and internships helps convert academic achievements into professional traction. The city’s evolving digital scene, combined with university support, creates a realistic bridge from advanced study to high-impact work.

Test: check whether Computer Science is the right major for you!

Computer Science

Answer all questions to see if a Master's in Computer Science is the right next step for you!

1. Do you want to deepen your expertise in advanced algorithms, data structures, and computational theory?

2. Are you aiming to work on cutting-edge topics like artificial intelligence, machine learning, or data science?

3. Do you want to build advanced software systems, contribute to scalable architectures, or work in systems programming?

4. Are you willing to engage in research projects (theoretical or applied) during your two-year master's studies?

5. Do you believe that a two-year master's in Computer Science will significantly enhance your career prospects or technical credibility?

6. Are you interested in specializing in areas like cybersecurity, cloud computing, or distributed systems?

7. Do you want to develop a stronger understanding of software engineering best practices, collaboration workflows, and version control in complex projects?

8. Are you excited about working with interdisciplinary teams combining computing with domains like biology, economics, or design?

9. Are you committed to ethical computing, understanding algorithmic bias, privacy, and responsible AI?

10. What most motivates you to pursue a Master’s in Computer Science?

Definitions and quotes

Computer
A computer is a device that can be instructed to carry out sequences of arithmetic or logical operations automatically via computer programming. Modern computers have the ability to follow generalized sets of operations, called programs. These programs enable computers to perform an extremely wide range of tasks.
Computer Science
Computer science is the study of the theory, experimentation, and engineering that form the basis for the design and use of computers. It is the scientific and practical approach to computation and its applications and the systematic study of the feasibility, structure, expression, and mechanization of the methodical procedures (or algorithms) that underlie the acquisition, representation, processing, storage, communication of, and access to, information. An alternate, more succinct definition of computer science is the study of automating algorithmic processes that scale. A computer scientist specializes in the theory of computation and the design of computational systems. See glossary of computer science.
Science
Science (from Latin scientia, meaning "knowledge") is a systematic enterprise that builds and organizes knowledge in the form of testable explanations and predictions about the universe.
Computer Science
[Computers] are developing so rapidly that even computer scientists cannot keep up with them. It must be bewildering to most mathematicians and engineers... In spite of the diversity of the applications, the methods of attacking the difficult problems with computers show a great unity, and the name of Computer Sciences is being attached to the discipline as it emerges. It must be understood, however, that this is still a young field whose structure is still nebulous. The student will find a great many more problems than answers.
George Forsythe (1961) "Engineering students must learn both computing and mathematics". J. Eng. Educ. 52 (1961), p. 177. as cited in (Knuth, 1972) According to Donald Knuth in this quote Forsythe coined the term "computer science".
Science
Today, when so much depends on our informed action, we as voters and taxpayers can no longer afford to confuse science and technology, to confound “pure” science and “applied” science.
Jacques-Yves Cousteau, in Jacques Cousteau and Susan Schiefelbein, The Human, the Orchid, and the Octopus: Exploring and Conserving Our Natural World (2007), 181.
Computer Science
Computer science is an empirical discipline. [...] Each new machine that is built is an experiment. Actually constructing the machine poses a question to nature; and we listen for the answer by observing the machine in operation and analyzing it by all analytical and measurement means available. Each new program that is built is an experiment. It poses a question to nature, and its behavior offers clues to an answer.
Allen Newell (1975) Computer Science as Empirical Inquiry: Symbols and Search. p. 114

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