Data Science and Analytics

Entry requirements

Months of entry

September

Course content

From social networks, ecommerce and government through to sensors, smart meters and mobile networks, data is being collected at an unprecedented speed and scale. But big data is of little use without 'big insight'. The skills required to develop such insight are in short supply and the shortage of skilled workers in the data analytics market is cited as a key barrier to unlocking everything that data has to offer.

The Data Science and Analytics MSc programme provides these skills, combining a strong academic degree course with hands-on experience of leading commercial technology, and the chance to gain industry certification. You will develop both your critical awareness of the very latest developments in data science and the practical skills that help you apply data science more effectively in a wide variety of sectors including finance, retail and government.

You’ll gain knowledge of key concepts and the nuances of effective data analysis. You’ll gain confidence in your own critical understanding of the challenges and issues arising from taking heterogeneous data at volume and scale, understanding what it represents, and turning that understanding into insight for business, scientific or social innovation. You’ll develop a practical understanding of the skills, tools and techniques necessary for the effective application of data science.

The course is designed to offer you the opportunity to gain hands-on experience in several data analytics tools (e.g. Hadoop, Spark, Tableau), programming languages (R, Python) and machine learning libraries.

A series of sessions in Python is offered to support students who are less familiar with programming.

You will also have the opportunity to obtain an SAS certificate such as SAS Base Programming, which is a recognised industry qualification, following a two-week SAS certification ‘boot camp’.

If you don’t want to commit to full or part-time study of the entire MSc, you can develop your educational portfolio over a longer period of time by undertaking staged study that leads to the award of Postgraduate Certificate (PGCert in Data Science), Postgraduate Diploma (PGDip in Data Science and Analytics) and Data Science and Analytics MSc in separate stages.

The roles that our graduates are typically recruited to within these organisations include analytics consultant, big data engineer/scientist, business analyst, clinical data scientist, data design specialist, data scientists, developer/development engineer, enterprise/technical architect, forecast analyst, marketing/customer and/or insight analyst, quantitative analyst and web analyst.

Brunel’s Women in Engineering and Computing mentoring scheme provides our female students with invaluable help and support from their industry mentors.

Information for international students

English language requirements

• IELTS: 6.5 (min 6 in all areas)
• Pearson: 59 (59 in all subscores)
• BrunELT: 63% (min 58% in all areas)
• TOEFL: 90 (min 20 in all)

You can find out more about the qualifications we accept on our English Language Requirements page.

Fees and funding

Learn more at the postgraduate funding page.