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MSci Data Science

City, University of London
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Course details
Course UCAS code: G102
Qualification type:
  • MSci, Full-time , Duration: 4 Years
Course Summary:
This degree is suitable for those who would like to develop creative computational solutions to derive the data-intensive transformation that is reshaping the way our society operates. It will build your foundational skills within computer science, such as algorithmic thinking and programming, and develop the specialist data scientists skills needed for the extraction of actionable insight from complex data collections. You should have a strong interest in technologies that produce and analyse data and will need to develop computational solutions for the acquisition and analysis of data, and use creative problem-solving skills to extract knowledge that can answer challenging questions in a domain of investigation. Data Science is a multidisciplinary domain that requires training in a wide-range of skills from programming to visualisation, to data analysis. The demand for data scientists in the UK has grown more than ten-fold in the past five years *. This programme aims to equip you with both strong foundational computer scientist skills and specialised data scientist skills. This powerful combination of computing and analytics will provide you a skill set that will be widely applicable not only within the computing industry but also in various application domains, from retail to health. The School has its own dedicated placements team with over 20 years of experience in providing on-hand placement and internship support as well as guidance for students throughout their studies. Placements are highly encouraged at City. Students that complete a placement year benefit from gaining professional experience working on real-life projects and are also more likely to achieve higher grades, secure a graduate-level job and earn a higher salary. The team also has longstanding relationships with an impressive and diverse range of companies spanning both large and small organisations including start-ups in Tech City and in particular organisations that are active in the big data and data science area such as: NHS, Facebook UK, Amazon UK, BBC, Tableau Software, Google, Microsoft, Cancer Reseaech UK, to name a few. Data scientists are employed in a range of businesses, from health to retail, or in government. The emphasis of the MSci (Hons) Data Science on areas that City has renowned research expertise, machine learning and visual analytics, and City's internships and links with many industrial partners will particularly enable you to gain appointments as specialists in data science, data analysis and visualisation in the security, health, transport and energy sectors, the creative industries, and a host of organisations within Tech City.
Modules:
The programme covers computer science starting with core foundational skills such as programming, and progressing to cover a range of computing topics with a focus on data science as a practice. The course covers the study and integration of advanced methods and techniques from knowledge representation and reasoning, statistical machine learning, high-performance computation, pattern recognition, service-oriented computing, computer programming, data warehousing, and data visualisation. A 450 hour individual project will allow you to carry out an extended piece of work under the supervision of one of our specialist academic and research staff, at the cutting edge of data science, in an industrial or academic context and will enable you to specialise in an application area of data science working often on a real-world problem. All Computer Science courses at City share a common first year. Students can select their final degree course at the end of the first year. In year two, you will take a further six core modules, each worth 15 credits, and undertake a team project worth 30 credits. In year three, you take five core modules and three electives, building the specialist Data Scientist skills. In year four, you take four core and one elective modules in addition to a large individual project (45 credits), researching and developing solutions in a data-intensive area of your own specialist interest.
Assessment Methods:
Most modules are assessed with examinations and coursework. Details can be found in the individual module specifications. Typically, modules are mainly assessed through written examination, and coursework also contributes to module assessment. The written examinations will contain theoretical questions, including mathematical aspects, as well as writing and analysing small amounts of code and small essays on the applications of computational techniques. As you move over to the more specialised modules as part of your Programme Stage-3 and Programme Stage-4, you will be expected to demonstrate how well you can synthesise various pieces of knowledge and be also assessed on how well you can critically reflect on the solutions you are suggesting. The balance of assessment by coursework (assessed essays and assignments) unseen examinations and a final year project will to some extent depend on the optional modules you choose. The approximate percentage of the course assessment is as follows: Year 1 48% written examination, 10% practical exams, 42% coursework Year 2 43% written examination, 4% practical exams, 53% coursework Year 3 56% written examination, 6% practical exams, 38% coursework. Year 4 35% written examination, 65% coursework.
Application deadline details:

15 January

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City is located in an amazing spot, hop on the tube at Angel or Barbican and you’ll be anywhere in Central London in minutes! London is such an exciting place to go to University, the possibilities are endless. The lecturers are passionate and knowledgeable, and the courses are really interactive and informative. The careers service was a massive help too, especially the CV appointments, so you'll feel really confident you'll be employed in graduate work after it’s all over.

 
Top TSR member reviews
  • acnh462's avatar by acnh462 on 7th October 2015
    It really helps other student in study and encourage them.
  • by Anonymous on 4th October 2015
    Really good facilities, perfect location, good quality of teaching and good career prospects.
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