Mathematics for Data Science with Placement BSc

Data analytics (Big Data) is a major phenomenon in the 21st century, rendering traditional data processing applications inadequate and increasing the demand for data analysts trained in this area who can collate, interpret and draw value from complex data sets.

This programme brings together a range of techniques that the modern data analyst needs. You will study blocks in mathematics, statistics, data analysis and computing, and tackle a variety of interesting and engaging problems from business and industry. A good grounding in all these subjects is essential for creating and using algorithms and systems that identify patterns and extract value from masses of data.

The course will also develop key graduate skills such as problem-solving and communication, with a third of the credits at each level based on project-oriented work where students will develop their knowledge, professionalism and creativity in a supporting environment.

As an example, in your second year you will be introduced to neural networks and deep learning. This important topic is at heart a powerful blend of linear algebra, nonlinear activation functions, vector calculus chain rule for gradients, and steepest descent optimisation with sampling. These fundamental building blocks will be brought together in theory and in software so that you will be able to build your own deep learning neural net, and be able to explain the function of every part of the algorithm. This last aspect of being able to explain the software’s function is key to the role of a mathematician as an understander as well as a user of methods, as opposed to just a consumer of software. The emphasis throughout will be on the practical rigour associated with getting deep learning to work.

Follow the four-year ‘Professional Placement’ degree programme and you‘ll benefit from our extensive experience in helping students to find well-paid work placements with blue-chip companies. Our sandwich students find that their mathematical and transferable skills are in demand in many sectors.

This programme strives to meet the educational requirements of the Chartered Mathematician designation, it is seeking an award by the Institute of Mathematics and its Applications. Once granted, when this course is followed by subsequent training and experience in employment to obtain equivalent competences to those specified by the Quality Assurance Agency (QAA) for taught master's degrees.

Typical Modules

Algorithms and their Applications
Calculus
Statistical Programming for Data Analytics
Decision Making in the Face of Risk
Stochastic Models
Scientific Computing

For a full list of modules please visit our website https://www.brunel.ac.uk/study/undergraduate/mathematics-for-data-science-bsc

The Mathematics for Data Science BSc programme uses elements of formative and summative assessment. Although both forms of assessment will be graded, only the summative assessment will count for progression for your final degree.

Our academics use formative assessment as a fundamental component in the learning process, including; class tests (both in paper and electronic format), electronic quizzes, and short written exercises. Summative assessments throughout this course consist of coursework and examinations.

We base your final degree class on your performance in second and final year. Final year carries twice the weight of second year.