Advertisement

cardiff university msc data science

Occasionally, the information found on the Internet is accurate, but it is not always the case. There is an abundance of information on the Internet, but not all of it is reliable. If you are searching for information about cardiff university msc data science, this article will provide you with the information you need.

Advertisement

Here’s some information you should know about the cardiff university msc data science, including the msc data science cardiff metropolitan university, cardiff university data science ranking, cardiff metropolitan university data science fees, msc data science and analytics and msc data science and analytics in uk. You will also find cardiff university msc data science related posts on collegelearners.

Why study this course

Acquire a range of in-demand skills for extracting and handling ‘big data’ and develop your practical skills through exposure to real-world problems and datasets.

Learn from our network of experts

We have a cross-disciplinary network of experts across the School of Mathematics, the School of Computer Science and Informatics andd other University research groups.

Industry experience

Gain valuable work experience on professional work placements and projects with leading data science practitioners in the UK and abroad.

Solve real-world problems

This course incorporates project-based learning using real-world datasets and problems.

New teaching facilities

Some of your modules will be taught in our newly-renovated Turing Suite.

Laptop provided

You will be provided with a laptop during induction week that will remain with you throughout the duration of the course.

This course will equip students with a theoretical understanding and practical experience of applying methods drawn from data science and analytics. You will develop a range of in-demand skills for extracting and handling ‘big data’ and applying modelling tools to help businesses and government organisations make better decisions.

On completion of the course, you will be well placed to progress into a variety of roles in data-intensive industries or a related research career.

This one-year degree falls under the umbrella of the Data Science Academy (DSA), run by the School of Computer Science and Informatics, in partnership with the School of Mathematics. You will benefit from the shared knowledge and skills of both Schools. However, your degree will still be run by the School of Mathematics. 

Where you’ll study

School of Computer Science and Informatics

Our degree programmes are shaped by multidisciplinary research, making them relevant to today’s employers and well placed to take advantage of tomorrow’s developments.

School of Mathematics

Our intellectually exciting degrees are accredited to meet the educational requirements of the Chartered Mathematician designation.

Admissions criteria

In order to apply, you must possess a minimum 2:2 degree from a recognised university in a numerate subject, such as mathematics, science, or engineering.

You should have a good standard of English, both written and oral. If your first language if not English, you should fulfil the University’s English language requirements (normally an IELTS score of 6.5, to include 5.5 in each sub-section).

Find out more about English language requirements.

Applicants who require a Student visa to study in the UK must present an acceptable English language qualification in order to meet UKVI (UK Visas and Immigration) requirements.

Criminal convictions

You are not required to complete a DBS (Disclosure Barring Service) check or provide a Certificate of Good Conduct to study this course.

If you are currently subject to any licence condition or monitoring restriction that could affect your ability to successfully complete your studies, you will be required to disclose your criminal record. Conditions include, but are not limited to:

  • access to computers or devices that can store images
  • use of internet and communication tools/devices
  • curfews
  • freedom of movement, including the ability to travel to outside of the UK or to undertake a placement/studies outside of Cardiff University
  • contact with people related to Cardiff University.

Tab to content

Course structure

This is a two-stage programme taught over one year for a total of 180 credits. The taught stage is 120 credits, followed by a 60-credit research project.

The modules shown are an example of the typical curriculum and will be reviewed prior to the 2021/22 academic year. The final modules will be published by September 2021.

You will undertake all 20-credit compulsory modules (100 credits in total) and choose a further 20 credits from a list of carefully selected optional modules. The 60-credit project undertaken in the summer will typically involve working with a company on a problem of real importance.Open all Core modules for year one

Module titleModule codeCredits
DissertationMAT09960 credits
Data VisualisationCMT21820 credits
Applied Machine LearningCMT30720 credits
Computational Data ScienceCMT30920 credits
Foundations of Operational Research and AnalyticsMAT02120 credits
Foundations of Statistics and Data ScienceMAT02220 credits

 Optional modules for year one

The University is committed to providing a wide range of module options where possible, but please be aware that whilst every effort is made to offer choice this may be limited in certain circumstances. This is due to the fact that some modules have limited numbers of places available, which are allocated on a first-come, first-served basis, while others have minimum student numbers required before they will run, to ensure that an appropriate quality of education can be delivered; some modules require students to have already taken particular subjects, and others are core or required on the programme you are taking. Modules may also be limited due to timetable clashes, and although the University works to minimise disruption to choice, we advise you to seek advice from the relevant School on the module choices available.Show less about the course structure Tab to content

Learning and assessment

How will I be taught?

The methods of teaching we employ will vary from module to module, as appropriate depending on the subject matter and the method of assessment. We teach using a mixture of lectures, seminars, computer workshops and tutorials.

Programming skills and the use of relevant software packages will be taught in our dedicated computer suites. We often invite industry experts to give presentations, which our students are welcome to attend.

We will allocate three supervisors to you for your dissertation project. Usually your supervisors will be two members of academic staff with an interest or specialism in your field of research and a sponsor supervisor from the organisation you will work with during your project. You should meet regularly with your supervisor throughout your project.

How will I be assessed?

We will assess your progress throughout the course. These assessments may take the form of written exam papers, in-module assignments, and the project dissertation, where knowledge and technical competence will be appraised.  We may also use group work, oral presentations and poster displays to test communication, critical thinking and problem-solving skills.

How will I be supported?

All of our students are allocated a personal tutor within both the School of Mathematics, and the School of Computer Science and Informatics when they enrol on the course. A personal tutor is there to support you during your studies, and can advise you on academic and personal matters that may be affecting you.

You will have access to the Trevithick Library, which holds our collection of mathematical and computer science-related resources, as well as to the other Cardiff University Libraries.

What skills will I practise and develop?

Knowledge & Understanding:

On successful completion of the Programme you will be able to demonstrate:  

  • A systematic understanding of knowledge, and a critical awareness of current problems and/or new insights, much of which is at, or informed by, the forefront of our academic discipline.

Intellectual Skills:

On successful completion of the Programme you will be able to demonstrate:

  • The ability to identify appropriate methods for the solution of problems in Data Science and Analytics.
  • Initiative and personal responsibility in decision-making in complex and unpredictable situations.
  • Systematic and creative methods for dealing with complex issues;  sound judgement making in the absence of complete data.

Professional Practical Skills:

On successful completion of the Programme you will be able to demonstrate:  

  • Advanced scholarship and practical experience in programming skills, data handling and extraction skills, machine learning and informatics skills, and problem solving and modelling skills
  • An ability to evaluate methodologies and develop critiques of them and, where appropriate, to propose new hypotheses.

Transferable/Key Skills:

On successful completion of the Programme you will be able to demonstrate:  

  • The ability to communicate ideas, principles and theories effectively by oral, written and practical means to both specialist and non-specialist audiences.
  • Effective working in a team and as an individual.
  • The ability to apply logical and analytic thinking to problems.

Show less about learning and assessment 

Tuition fees

Students from the UK

Tuition fee (2021/22)Deposit
£9,700None

Students from the EU, EEA and Switzerland

EU, EEA and Swiss nationals starting in 2020/21 will pay the same tuition fee as UK students for the duration of their course.

If you are an EU/EEA/Swiss national, unless you qualify for UK fee status, tuition fees for 2021/22 will be in line with the fees charged for international students. UKCISA have provided information about Brexit and tuition fees.

Students from the rest of the world (international)

Tuition fee (2021/22)Deposit
£22,950£1,000

More information about tuition fees and deposits, including for part-time and continuing students.

Financial support

Financial support may be available to individuals who meet certain criteria. For more information visit our funding section. Please note that these sources of financial support are limited and therefore not everyone who meets the criteria are guaranteed to receive the support.

Additional costs

The University considers that the following costs do not need to be covered by schools as they are either not essential or are basic costs that a student should be expected to cover themselves:

  • Calculators
  • General stationery
  • Text books (assumed to be available in the library)
  • Non-essential copying / printing.

If there are optional costs/fees to be covered by the student, these are not a requirement to pass the degree. The exception to this is the cost of printing and binding of the final dissertation for submission, which must be paid for by the student.

Will I need any specific equipment to study this course/programme?

We will provide equipment that is essential to the course. We recommend, however, that you bring some basic drawing equipment.

You will be given access to all relevant IT-related software and equipment on our networked computers. As well as computer labs for master’s students, we have an MSc Reading Room, in which resources are made available and where master’s level students can meet, socialise and work together.

.

Living costs

We’re based in one of the UK’s most affordable cities. Find out more about living costs in Cardiff.

Careers and placements

The skills you gain during the programme will equip you for graduate roles in this field. Previous postgraduates have gone on to work with a variety of companies and Government organisations including the Office for National Statistics, Lloyds Banking Group, Nationwide, British Airways, Network Rail, UK Government, The Financial Times, Virgin Media, Welsh Water and Admiral Insurance.

Placements

A three-month placement for the student’s dissertation project, based with one of our industrial partners in the UK or abroad.

Leave a Reply

Your email address will not be published. Required fields are marked *

You May Also Like