Study Programmes and Branches of Master Studies

for the Academic Year 2019/2020


Study Programme Computer Science

Computational Linguistics

Form of study: full-time

Outline of study: The aim of the Computational Linguistics programme is prepare students for research in the area of natural language processing and the development of applications dealing with both written and spoken language. Examples of such applications are systems of information retrieval, machine translation, grammar checking, text summarization and information extraction, automatic speech recognition, voice control, spoken dialogue systems, and speech synthesis.

Prospects for graduates: The graduate student is an expert in the application of state-of-the-art statistical as well as rule-based methods in the area of natural language processing. The student is prepared for doctoral studies in this area and for development of software applications of natural language processing such as information retrieval, question answering, summarization and information extraction, machine translation, automatic construction of dictionaries, speech processing (in Czech and other natural languages). Given the general applicability of machine learning and data-driven methods, the graduate is also well-equipped to use these methods in other domains, such as finance, medicine, and other areas where large quantities of both structured and unstructured data are analysed. The graduate has also extensive programming skills.

Details of study:

Discrete Models and Algorithms

Form of study: full-time

Outline of study: The study plans Discrete Mathematics and Combinatorial Optimization and Mathematical Structures in Computer Science provide advanced knowledge in the fields of applied mathematics and computer science. An emphasize is put on up-to-date theoretical and applied questions in the area. The study plans Optimization and Mathematical Economics provide skills to solve difficult technical and economical problems with the use of optimization methods and suitable methods from mathematical economics.

Prospects for graduates: Graduates have a broad range of possibilities to work in areas connected with applied mathematics and computer science. Graduates are able to solve complicated technical and economic decision problems. Solutions of these problems are based on methods of mathematical optimization and on methods solving conflict situations. A deep knowledge of modern mathematical methods enables the graduate to design mathematical models in complicated economic situations. An education in computer science provides skills to effectively implement the solutions with the use of fast computers.

Details of study:

Software Systems

Form of study: full-time

Outline of study: The study branch Software Systems puts an emphasis on system-oriented programming in one of three focus domains. The System Programming domain focuses on coding the basic layers of a computer system (middleware, operating system). In the Dependable Systems domain, the curriculum deals with the systematic construction of systems with high reliability, such as embedded and real-time systems. The High Performance Computing branch introduces techniques for software development on high performance computing systems (highly parallel systems, distributed systems, clouds). All focus domains pay attention to both the programming tools and methods and the associated architectural knowledge.

Prospects for graduates: Graduates have an expertise in the team development of software systems, their analysis, design, implementation and deployment in the real world, including evaluation. They acquire during their studies the ability to react flexibly to the continual advancement of new technologies. They gain knowledge of database systems, architectures and principles of system environments and software systems, modern internet technologies, computer graphics etc.

Details of study:

Theoretical Computer Science

Form of study: full-time

Outline of study: The goal of the study programme Theoretical Computer Science is to prepare graduates with a deep and sufficiently broad background in computer science which is based on mastering its theoretical foundations. These foundations are extended by specialized courses giving graduates a good overview of areas of computer science such as complexity and computability, design and analysis of algorithms, and artificial intelligence. This deep theoretical knowledge then allows graduates to more quickly absorb new findings in the developing areas of computer science and to actively contribute to the advancement of the state-of-the-art.

Prospects for graduates: Graduates may work in research and development in the area of software production for industrial applications, state administration, and in consulting companies. They can work in any position that requires logical thinking, analytical capabilities, an algorithmic approach to problem solving, and the exploitation of modern methods of computer science (artificial intelligence, knowledge representation, declarative programming, machine learning, biologically inspired paradigms, and multi-agent systems). Graduates may also work at a university and continue studies for a PhD. The education acquired also permits graduates to work as programmers in any position.

Details of study:

 

Charles University, Faculty of Mathematics and Physics
Ke Karlovu 3, 121 16 Praha 2, Czech Republic
VAT ID: CZ00216208

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