MSc Data Science

Data science is rapidly emerging in organisations and the need for fully trained data scientists, analysts and programmers are in demand now more than ever. Businesses rely on big data to uncover hidden patterns and unknown correlations to make informed decisions and drive business success. On the Data Science course, you will learn how to apply high-level analytical skills and knowledge to solve a range of real-world problems.

The MSc Data Science is designed to support your development of transferable skills and expertise to play a leading role at a technical and practical level in the industry. Additionally, you will work towards a globally recognised qualification, the SAS Joint Certificate in Applied Statistics and Data Mining. The Joint Certificate will validate your skills and ability to use SAS software, giving you a competitive advantage in the job market. 

To hear how the Data Science course has benefitted our graduates, visit the Data Science subject page.

2022/23 update: Blended learning approach for USW courses.

[Update excludes online-only courses].

The wellbeing and health and safety of our students and staff is paramount to us. We are committed to delivering all of our courses and services as safely as possible. Due to the Covid-19 pandemic, the methods and activities adopted for delivering our courses in the coming year may differ from those previously published and may be subject to change during the course of your study if such change is necessary due to public health concerns, health and safety guidance or in response to Government Guidelines. Whether you’re on-campus full time, part-time with online study, or full-time online, USW is committed to providing you with a fantastic student experience and a wealth of support, and you can hear how students have benefitted from this approach here: Learn more about blended learning.

Study Mode
2022
Duration Start Date Campus Campus Code
Full-time 1 Year September Treforest A
Part-time 2 Years September Treforest A
Study Mode
2023
Duration Start Date Campus Campus Code
Full-time 1 Year September Treforest A
Part-time 2 Years September Treforest A

The MSc Data Science has six core taught modules divided into two streams. At the beginning of each stream you will be taught the fundamentals of applied statistics, computing technology, programming and data base systems. Your existing analytical and technical skills will be developed to understand how to use the industry software used in the workplace, in turn preparing you for your individual research project.

Stream One: MSc Data Science

  • Applied statistics for data science
  • Data mining and statistical forecasting
  • Project management and research methodology

Stream Two: MSc Data Science

  • Principles of computing
  • Applied Machine Learning and Deep Learning
  • Big data engineering and applications

Alongside these modules, you will complete an individual research project. Your project will be proposed and supported by local employers across a range of industries. Previous project partners include Admiral, Dwr Cymru, EY, NHS Wales, Public Health Wales, Velindre Cancer Care Trust, Talent Intuition and the Met Office.

Teaching

The MSc Data Science course is delivered through a series of practical classes and workshops where you will have the opportunity to put into practice what you have learnt via hands-on exercises and design projects.

The Data Science Masters offers a flexible approach to learning, allowing you to study full-time, part-time or through continuing professional development (CPD) for working professionals. The CPD route is an accessible pathway for employers to equip staff with further training opportunities to work towards a postgraduate qualification.

You will be taught by active researchers and leading professionals exposing you to current real-world problems, methodologies, and industry-standard techniques and software.

Full-time students will typically spend 12 hours in classes each week. For those studying part-time, this is reduced to six hours each week.

Each stream is delivered on a single day per week.

Stream One runs on a Wednesday and Stream Two on a Friday. Full-time students will undertake both streams in one year whilst a part-time student will start on Stream One in Year One and then move on to Stream Two in Year Two.

Students undertake one module at a time for each stream and each module within a stream runs across three consecutive eight-week blocks.

All students will also undertake a 60-credit individual project. Typically, a full-time student will work on the individual project from June-September.

A part-time student will have the opportunity to start work on their individual project during the first summer and will finish their individual project during the second summer completing by the September of Year Two.

 

 

Assessment

All modules are assessed entirely through coursework based activities ranging from reports, demonstrations, presentations and coding tasks.

Facilities

In industry, computing power is now vital to aid complex mathematical calculations on a daily basis. Therefore, throughout your Masters degree in Data Science, you will be exposed to a variety of key industry computer packages to facilitate your learning. You will also be taught sought-after programming skills.

Practice is so important in gaining understanding of complex data science techniques, which is why we have a dedicated Data Science computer laboratories and access to student workrooms dedicated to our Data Science students. These facilitate a learning environment where you can work individually or in groups and as they are located next to the staff offices you will have no problem finding help if you get stuck.

Featured Lecturer:
Dr Penny Holborn

Dr Penny Holborn

Dr Penny Holborn is a data scientist whose expertise lies in applying analytical techniques to solve real world problem

Her previous work has involved working in healthcare modelling in collaboration with Aneurin Bevan University Health Board, using a range of analytical techniques to improve utilisation and efficiency across a number of key services. She continues to work on projects across the local Health Boards including recent work predicting bed numbers for the Critical Care Unit at the Royal Gwent Hospital.

Dr Holborn is actively involved in promoting and ensuring equality across the University and the wider subject discipline and is a member of the USW Athena Swan team and the Wales Women in STEM network. Find her latest research on the Maths Research site.

We regularly revalidate courses for quality assurance and enhancement

At USW, we regularly review our courses in response to changing patterns of employment and skills demand to ensure we offer learning designed to reflect today’s student needs and tomorrow’s employer demands.

If during a review process course content is significantly changed, we’ll write to inform you and talk you through the changes for the coming year. But whatever the outcome, we aim to equip our students with the skillset and the mindset to succeed whatever tomorrow may bring. Your future, future-proofed.

Suitable for graduates with a minimum 2:2 Honours degree or equivalent in a numerate discipline across any STEM or business subject. Relevant industry experience can also be taken into account.

 

The course welcomes international applicants and requires an English level of IELTS 6.0 with a minimum of 5.5 in each component or equivalent.

Full-time fees are per year. Part-time fees are per 20 credits. Once enrolled, the fee will remain at the same rate throughout the duration of your study on this course.

August 2022 - July 2023 Fees


  • Full-time UK: TBC

  • Full-time International:  £14700 

  • Part-time UK: TBC

August 2023 - July 2024 Fees


  • Full-time UK: TBC

  • Full-time International: TBC

  • Part-time UK: TBC

Student Perks

At the University of South Wales, you’re investing in so much more than a degree. We strive to provide our students with the best possible experience, no matter what you chose to study. Whether it’s access to top of the range mac books and PCs, state-of-the-art facilities packed with industry-leading equipment and software, masterclasses and events led by industry experts, or a wide range of clubs and societies to meet likeminded people, better tomorrows start with extra perks.

Each course also has their own unique student benefits to prepare you for the real word, and details of these can be found on our course pages. From global field trips, integrated work experience and free course-related resources, to funded initiatives, projects working with real employers, and opportunities for extra qualifications and accreditations - at USW your future, is future proofed.

Click here to learn more about student perks at USW.

Additional Costs

As a student of USW, you’ll have access to lots of free resources to support your study and learning, such as textbooks, publications, online journals, laptops, and plenty of remote-access resources. Whilst in most cases these resources are more than sufficient in supporting you with completing your course, additional costs, both obligatory and optional, may be required or requested for the likes of travel, memberships, experience days, stationery, printing, or equipment. Below we’ve listed what types of additional costs are associated with this course:

Funding

The University of South Wales is offering a 20% reduction in tuition fees for all University of South Wales* graduates starting a taught/online*** MA, MSc, LLM, MBA, DBA course or a PcET/PGCE course from September 2022 (this includes students starting their course in January/February 2023).

Apply directly to the University for this course

Admissions statement 

Employment prospects are strong in this rapidly growing and demanding industry. There are a number of careers available to those trained in data science - students could go on to be data scientists, statistics officers, business analysts, predictive modellers or computer programmers, these will continue to grow as organisations are required to adapt to improving technologies.

Graduates may also progress on to a PhD or research degree.