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City, University of London

Data Science

UCAS Code: G102

Master of Science - MSci

Entry requirements


A level

A,B,B

Extended Project Qualification (EPQ): We welcome applications that include the EPQ. Where relevant, this may be included in our offer, resulting in an 'A' Level offer reduced by one grade

GCSE/National 4/National 5

GCSE: A minimum of grade 4 (C) in GCSE English and a minimum of grade 6 (B) in GCSE Mathematics.

International Baccalaureate Diploma Programme

32

IB: 32 points total including Higher Level subjects at grade 6

Pearson BTEC Level 3 National Extended Diploma (first teaching from September 2016)

D*DD

Btec (IT/numerate subjects only)

UCAS Tariff

128

GCE A levels ABB (Computer Science, Mathematics or Physics preferred)

About this course


Course option

4.0years

Full-time | 2020

Subject

Computer science

**This course is subject to final internal approval**

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.

Assessment weightings by year
? Year 2: 20% ? Year 3: 40% ? Year 4: 40%

The Uni


Course location:

City, University of London

Department:

Computer Science

TEF rating:
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What students say


We've crunched the numbers to see if overall student satisfaction here is high, medium or low compared to students studying this subject(s) at other universities.

70%
med
Computer science

How do students rate their degree experience?

The stats below relate to the general subject area/s at this university, not this specific course. We show this where there isn’t enough data about the course, or where this is the most detailed info available to us.

Computer science

Teaching and learning

68%
Staff make the subject interesting
84%
Staff are good at explaining things
69%
Ideas and concepts are explored in-depth
77%
Opportunities to apply what I've learned

Assessment and feedback

Feedback on work has been timely
Feedback on work has been helpful
Staff are contactable when needed
Good advice available when making study choices

Resources and organisation

77%
Library resources
81%
IT resources
82%
Course specific equipment and facilities
53%
Course is well organised and has run smoothly

Student voice

Staff value students' opinions

Who studies this subject and how do they get on?

83%
UK students
17%
International students
84%
Male students
16%
Female students
69%
2:1 or above
17%
Drop out rate

After graduation


The stats in this section relate to the general subject area/s at this university – not this specific course. We show this where there isn't enough data about the course, or where this is the most detailed info available to us.

Computer science

What are graduates doing after six months?

This is what graduates told us they were doing (and earning), shortly after completing their course. We've crunched the numbers to show you if these immediate prospects are high, medium or low, compared to those studying this subject/s at other universities.

£27,300
med
Average annual salary
75%
low
Employed or in further education
89%
med
Employed in a role where degree was essential or beneficial

Top job areas of graduates

62%
Information technology and telecommunications professionals
12%
Information technology technicians
8%
Engineering professionals

This is a newly-classified subject area for this kind of data, so we don’t currently have very much information to display or analyse yet. The subject is linked to important and growing computing industries, and over time we can expect more students to study them — there could be opportunities that open up for graduates in these subjects as the economy develops over the next few years.

What about your long term prospects?

Looking further ahead, below is a rough guide for what graduates went on to earn.

Computer science

The graph shows median earnings of graduates who achieved a degree in this subject area one, three and five years after graduating from here.

£26k

£26k

£32k

£32k

£34k

£34k

Note: this data only looks at employees (and not those who are self-employed or also studying) and covers a broad sample of graduates and the various paths they've taken, which might not always be a direct result of their degree.

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This is the percentage of applicants to this course who received an offer last year, through Ucas.

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This is what the university has told Ucas about the course. Use it to get a quick idea about what makes it unique compared to similar courses, elsewhere.

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Course location and department:

This is what the university has told Ucas about the course. Use it to get a quick idea about what makes it unique compared to similar courses, elsewhere.

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Teaching Excellence Framework (TEF):

We've received this information from the Department for Education, via Ucas. This is how the university as a whole has been rated for its quality of teaching: gold silver or bronze. Note, not all universities have taken part in the TEF.

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This information comes from the National Student Survey, an annual student survey of final-year students. You can use this to see how satisfied students studying this subject area at this university, are (not the individual course).

We calculate a mean rating of all responses to indicate whether this is high, medium or low compared to the same subject area at other universities.

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This information is from the Higher Education Statistics Agency (HESA).

You can use this to get an idea of who you might share a lecture with and how they progressed in this subject, here. It's also worth comparing typical A-level subjects and grades students achieved with the current course entry requirements; similarities or differences here could indicate how flexible (or not) a university might be.

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Post-six month graduation stats:

This is from the Destinations of Leavers from Higher Education Survey, based on responses from graduates who studied the same subject area here.

It offers a snapshot of what grads went on to do six months later, what they were earning on average, and whether they felt their degree helped them obtain a 'graduate role'. We calculate a mean rating to indicate if this is high, medium or low compared to other universities.

Have a question about this info? Learn more here

Graduate field commentary:

The Higher Education Careers Services Unit have provided some further context for all graduates in this subject area, including details that numbers alone might not show

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The Longitudinal Educational Outcomes dataset combines HRMC earnings data with student records from the Higher Education Statistics Agency.

While there are lots of factors at play when it comes to your future earnings, use this as a rough timeline of what graduates in this subject area were earning on average one, three and five years later. Can you see a steady increase in salary, or did grads need some experience under their belt before seeing a nice bump up in their pay packet?

Have a question about this info? Learn more here