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Data analytics (Big Data) is a major phenomenon in the 21st century, there is an increasing 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 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 supportive 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.
Program overview
Main Subject
Mathematics
Degree
BSc
Study Level
Undergraduate
Study Mode
On Campus
Data analytics (Big Data) is a major phenomenon in the 21st century, there is an increasing 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 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 supportive 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.
Admission Requirements
6+
59+
77+
30+
26+
1240+
3 Years
Sep
Tuition Fee
Domestic Students
9,535 GBP
-
International Students
22,320 GBP
-
Scholarships
One of the important factors when considering a master's degree is the cost of study. Luckily, there are many options available to help students fund their master's programme. Download your copy of the Scholarship Guide to find out which scholarships from around the world could be available to you, and how to apply for them.
Mathematics for Data Science BSc
Brunel University of London, London, United Kingdom
# 501-550QS Subject Rankings
36 monthsProgram duration
22,320 GBPTuition Fee/year
YesScholarships
Program overview
Main Subject
Mathematics
Degree
BSc
Study Level
Undergraduate
Study Mode
On Campus
This programme brings together a range of techniques that 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 supportive 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.
Program overview
Main Subject
Mathematics
Degree
BSc
Study Level
Undergraduate
Study Mode
On Campus
This programme brings together a range of techniques that 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 supportive 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.
Admission Requirements
Tuition Fee
Domestic Students
International Students
Scholarships
One of the important factors when considering a master's degree is the cost of study. Luckily, there are many options available to help students fund their master's programme. Download your copy of the Scholarship Guide to find out which scholarships from around the world could be available to you, and how to apply for them.
In this guide you will find:
Where to look for scholarship opportunities
How to apply to scholarships relevant to you
A list of available scholarships around the world
A scholarship application checklist
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