Overview Data Scientist is in the top-ten of emerging jobs according to the LinkedIn emerging jobs report. Graduates that can combine their mathematical skills and statistical modelling to make sense of big data are in high demand. Studying BSc Mathematics and Data Science with us will provide a platform for you to enter this important sector. Additionally, as a Mathematics graduate you can find employment in any number of different careers including IT, finance and teaching. Why study BSc Mathematics and Data Science at Middlesex University? We believe strongly that the work you do must be relevant to the world of work – that's why our course has a strong practical slant. The core focus of your degree will be understanding the mathematical theory underpinning data science and learning within a practical setting to develop key skills for future employment. This degree offers an opportunity to obtain practical real-life experience of working and analysing big data, in addition to being taught and supported by staff that work and research in all areas of mathematics, with expert knowledge from the industry. You’ll build on theory to deliver practical solutions to a variety of real-world big data problems. The project-based assessment will give you a practical education and prepare you to apply your mathematical skills to one of the top emerging job sectors. Throughout your degree there will be scope to develop your programming and software skills, as well as learn new skills within a work environment through placement opportunities. Course highlights Modules that teach techniques from machine learning and artificial intelligence Project and coursework based assessment, no end-of-year exams Large, 60 credit third year project allows you to demonstrate the accumulation of your knowledge to develop a significant piece of work.
Year 1 Calculus and Geometry (30 credits) - Compulsory Mathematical Thinking (15 credits) - Compulsory Introduction to Programming (15 credits) - Compulsory Probability and Data Analysis (30 credits) - Compulsory Mathematical Models (15 credits) - Compulsory Linear Algebra (15 credits) - Compulsory Year 2 Problem Solving and Communication (30 credits) - Compulsory Software Design (15 credits) - Compulsory Discrete Mathematics (15 credits) - Compulsory Mathematics of Machine Learning (15 credits) - Compulsory Mathematical Statistics (30 credits) - Compulsory Advanced Calculus (15 credits) - Compulsory Year 3 Neural Networks and Deep Learning (30 credits) - Compulsory Mathematical Techniques for Optimisation (15 credits) - Optional Data Mining (15 credits) - Optional Time Series (15 credits) - Optional Cryptography and Blockchain (15 credits) - Optional Stochastic Processes for Finance (15 credits) - Optional Graph Theory (15 credits) - Optional Project (30 credits) - Compulsory
How to apply
This is the deadline for applications to be completed and sent for this course. If the university or college still has places available you can apply after this date, but your application is not guaranteed to be considered.
Points of entry
The following entry points are available for this course:
- Year 1
- Year 2
- Year 3
- Year 4
- Year 5
- Year 6
Entry requirements listed are accurate at the time of publishing and vary between programmes. Please check your chosen course page for specific entry requirements. Depending on your chosen course, we also consider a combination of qualifications. The latest entry requirements can be found on the course page at: https://www.mdx.ac.uk/courses/undergraduate/mathematics-data-science We have a personalised admissions approach in which we make fair, but aspirational offers to our applicants. We feel it’s important that you continue to aim high and achieve great results. If you don’t quite make the grades you hoped to, we’ll look at more than your qualifications when making our final decision. We’ll take into consideration any barriers you may have faced in your learning, especially with potential disruption due to the coronavirus, your achievements in other areas and your personal statement. At Middlesex, we’ll always aim to be as flexible as possible. We pride ourselves on how we recognise potential in our applicants, and support them to succeed in the future.
Please click the following link to find out more about qualification requirements for this course
English language requirements
|With a minimum of 5.5 in each component
|With at least 17 in listening & writing, 20 in speaking and 18 in reading
|6.0 (with minimum 5.5 in all components
Visit our general entry requirements page, by clicking on the link below, to see how these points can be achieved from our acceptable level 3 qualifications and the combinations which are welcomed by Middlesex University, including GCSE requirements.
There is no data available for this course. For further information visit the Discover Uni website.
Fees and funding