Intensive (12 - 15 months) or Standard (24 - 27 months)
Distance Learning option available
Start September or February
The MSc Computing programme is designed for graduates and working professionals. Building on existing knowledge and skills, you will master cutting-edge technologies as well as the critical skills of negotiation and project management. You will also develop the intellectual ability for abstract analysis and synthesis, helping you to make reasoned, critical decisions for selecting or implementing appropriate computer-based solutions. Successful graduates are well-prepared to make an immediate contribution to major projects at the leading edge of computer applications.
Teaching and learning are highly experiential, underpinned by practical projects, fieldwork, business simulations and case studies. You will enjoy unprecedented access to an outstanding group of lecturers who deliver relevant research-based teaching, feedback, consultation and support. The Master’s programme is supported by regular guest lectures as well as the Media Innovation and Technology Series interdisciplinary lecture series.
* Intensive Format option. Modules in Standard Format are spread over 4 semesters, plus the Dissertation.
The programme has two modes of study.
Two semesters of study plus one semester of dissertation undertaken within 12 to 15 months.
Four semesters of study plus one semester of dissertation undertaken in 24-27 months.
The Distance Learning Master’s Degree offers maximum flexibility, regardless of your location. The combination of regular studies in our immersive Digital Campus, supplemented by in-person residential workshops in Prague, gives you the opportunity to achieve your goal within as little as 12 months. Delivery of the programme via the Digital Campus allows for individual mentoring from our professional lecturers and for active participation and discussion with your fellow students.
The MSc in Computing culminates in a challenging, self-defined dissertation project that taps into each student's strengths, interests and experiences, as shown in the examples below and which include links to the student's full dissertations.
Serverless functions allocation in IoT using machine learning →
‘The IoT (Internet Of Things) comprises a network of smart devices that can transfer data either between each other or between layers in a network. Initially, the IoT has faced high latency problems by using only cloud computing solutions. Recently,'fog' computing has emerged, which aims to move computational tasks closer to the edge. However, the introduction of serverless computing has produced its own challenges concerning the allocation of functions between the fog and cloud layers. We propose a prediction-based framework that will choose where each function will be executed based on its execution history. The decision will be made using a machine-learning model, which will be trained and tested based on input features.’
WebSocket Protocol Performance for Real Time Cryptocurrency Algorithmic Trading →
Most cryptocurrency exchanges provide market data via WebSocket API, and trading systems are therefore recommended to use the WebSocket protocol to connect to the exchange and receive data. Various programming languages and their respective libraries can be used to develop a communication interface within the trading system. This study evaluates performance differences in communication speed - an important criterion for profitable trading systems. Six connectors were developed (in compiled, intermediate and interpreted programming languages and their respective WebSocket libraries) and deployed in the cloud.
Management and governance are essential activities for Non-Profit Organizations (NPOs), but also highly complex due to the nature of the sector. The use of a framework can provide the organizations with guidance and help their Boards or other strategic bodies to understand the organization’s current direction, what to expect from it and what needs to be done. The research explores to what degree the COBIT 5 framework is suitable for an NPO, and also suggests a number of tools that can be used by the organization in making decisions concerning the framework's compatibility with the organization’s inner workings.
Petr Roudenský, an alum of PCU, is currently pursuing his PhD at The University of Sheffield in the United Kingdom, where he is conducting further research on neurodegenerative diseases, in particular Huntington's Disease.
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