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How you'll learn – University of Reading

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  • Learn from our experts

    Study in a supportive and flexible environment

How you'll learn

Learn from Computer Science experts. Our lecturers have expertise across a broad range of areas. Their knowledge and familiarity with industry requirements inform your learning experience.

Study in a supportive, flexible environment that focuses on both theoretical and practical skills. Our courses are fully accredited, and we have close links both with industry and other departments – giving you the best preparation possible for your future career.

Courses developed with an Industrial Advisory Board

Major international companies are actively involved in the development and review of our courses through our Industrial Advisory Board. Companies currently participating are Eli Lilly, Nationwide Building Society, Sony, Microsoft and IBM.

The Industrial Advisory Board contributes to the strategic development of Reading's provision for Computer Science students in the 21st century. Working together, we develop the teaching, equipment, software, and work experience to prepare students for their future careers. The Board provides a valuable view of what the future looks like from an external perspective, enhancing the employability of our graduates by supporting a learning experience which develops the evolving technical and soft skills required in the industry.

Accredited by relevant professional bodies

The BSc Computer Science and BSc Computer Science with Industrial Year are accredited by the British Computer Society (BCS), the chartered institute for IT. The BSc Mathematics with Computer Science and BSc Mathematics with Computer Science with Placement Year are accredited by the Institute of Mathematics and its Applications (IMA).

learn theory and practice

Our teaching combines theory with practice. This blend enables you to balance a theoretical understanding of the subject with the practical and transferable skills required to advance in your career. You will be taught core topics essential for accreditation, but will also have the flexibility to tailor your studies to your interests through your choice of optional modules.

Advance through your course of study, and you'll find class sizes reduce as students choose optional modules in their specific areas of interest. This increase in the ratio of staff to students is beneficial when tackling more complex material in your degree during your crucial final year.

Facilities and resources

Study in dedicated computing laboratories, with workstations running both Windows and Linux operating systems. You will have access to 200 workstations with a virtual infrastructure for remote connection to a secure virtual private network, a walk-in immersive virtual reality system and a big data computing cluster.

our learning community

Take advantage of Peer-Assisted Learning opportunities and drop-in sessions; our final year students provide optional additional support sessions during your first year. Evidence from universities around the world that actively encourage Peer-Assisted Learning shows huge benefits for the students involved.

Our staff also have weekly drop-in sessions, and open-door policies – so help is never far away.  

academic tutorials

You will attend regular academic tutorials in your first year. These are hour-long sessions in which each tutor meets with all their students. A good relationship with your tutor is important as he or she can then provide you with the exact support you need during your course of study. They can also write more personalised references for placements and job applications towards the end of your degree.  

build complementary strengths

Our Department is based within the School of Mathematical, Physical and Computational Sciences, in the vicinity of both the Department of Mathematics and Statistics and the Department of Meteorology. Benefit from the many complementary strengths across the departments, including:

  • Specific expertise relating to big data
  • Data visualisation and analytics
  • Applications of high-performance computing to weather prediction and climate simulation.

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