Master of Science - Data Science and Analytics

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. Students will develop both their critical awareness of the very latest developments in data science and the practical skills that help them apply data science more effectively in a wide variety of sectors including finance, retail and government.

Students will gain knowledge of key concepts and the nuances of effective data analysis. Students will gain confidence in their 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. Students will develop a practical understanding of the skills, tools and techniques necessary for the effective application of data science.

The course is designed to offer students 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.

Students 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’.

The MSc in Data Science and Analytics will be a good fit for those who are curious to learn how to use data to answer interesting questions, want to learn how to apply data science software tools (such as R Studio or Python) to solve problems, are interested in the ethical aspects and governance that handling data requires and want to acquire skills to report and present their analysis results.

The roles that Brunel 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 their female students with invaluable help and support from their industry mentors.