This specialist Master’s in Data Science provides a theoretical knowledge of data science alongside the practical skills that will help you prosper in the jobs market.
You’ll be exposed to a broad range of topics such as data science, statistics, specialist programming, machine learning and data visualisation. .
What you should know about this course
- You will learn about many interesting topics in modern data science statistics, data visualisation, programming, machine learning, and data visualisation, plus application areas such as business intelligence.
- We will provide you with the necessary tools to understand the in-depth theory behind data science and artificial intelligence.
- Gain practical skills for careers within this specialised field.
What you will study
Year 1
Students are required to study the following compulsory modules.
- MSc Project (60 credits)
- Big Data (15 credits)
- Data Visualisation (15 credits)
- Machine Learning (15 credits)
- Applied Machine Learning (15 credits)
- Programming Fundamentals for Data Science (15 credits)
- Essential Professional and Academic Skills for Masters Students
- Statistical Techniques and Time Series (15 credits)
Students are required to choose 15 credits from this list of options.
- Clouds, Grids and Virtualisation (15 credits)
- Blockchain for FinTech Applications (15 credits)
Students are required to choose 15 credits from this list of options.
- Technologies for Anti-Money Laundering and Financial Crime (15 credits)
- Graph and Modern Databases (15 credits)
How you will learn
Teaching
In a typical week, learning takes place through a combination of lectures, tutorials and practical work in the labs. You’ll be able to discuss and develop your understanding of topics covered in lectures in smaller group sessions, and to put your knowledge into practice in our specialist computer laboratories.
Teaching hours may fall between 9am and 9pm, depending on your elective courses and tutorials.
Class sizes
Lectures are usually attended by larger groups and seminars/tutorials by smaller groups. This can vary more widely for modules that are shared between degrees.
Independent learning
Outside of timetabled sessions, you’ll need to dedicate time to self-study to complete coursework, and prepare for presentations and exams. Our Stockwell Street library and online resources will support your further reading and research.
You can also join a range of student societies, including our Computer and Technology Society, Gre Cyber Sec, Forensic Science Society, and Games Development Society.
Overall workload
Your overall workload consists of lectures, tutorials, labs, independent learning, and assessments. For full-time students, the workload should be roughly equivalent to a full-time job. For part-time students, this will reduce in proportion with the number of modules you are studying.
Assessment
On this course, students are assessed by coursework, examinations and a project. Some modules may also include practice assessments, presentations, demonstrations, and reports, which help you to monitor progress and make continual improvement.
Feedback summary
We aim to give feedback on assignments within 15 working days.
Dates and timetables
The academic year runs from September to the end of August, as the students are working on their project full-time during the summer months.
Zobacz więcej na stronie uniwersytetu >>
Wiza studencka do Wielkiej Brytanii
Aby studiować w Wielkiej Brytanii potrzebujesz wizy studenckiej. Aby złożyć wniosek o taką wizę studencką musisz zdjać certyfikat językowy na poziomie B2.
Uważaj! Do celów wizowych musisz wybrać wyłącznie egzamin w wesji Secure English Language Test (SELT) UKVI .
Co to jest test SELT UK VI registration? Przeczytaj więcej o testach SELT UKVI >>
