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Data Science (with an industrial placement year) MSc

Data Science (with an industrial placement year) MSc

Different course options

Study mode

Full time

Duration

4 years

Start date

SEP-26

Key information
DATA SOURCE : IDP Connect

Qualification type

MSc - Master of Science

Subject areas

Data Science

Course Summary

Data forms the basis of knowledge, and underpins our understanding of the world. We can find data everywhere – in how we exercise, what we eat, and even in how galaxies evolve. From agriculture to astronomy, the rate at which we collect and process information is accelerating. Data Science helps us interrogate this information to solve problems. You'll learn to create more effective systems and make the world a better place. Get the tools and techniques you need to build, analyse and interpret large datasets common to academic science and industrial practice. By studying at Sussex, you will: • gain hands-on experience with large-scale, real-world datasets, learning how to develop robust and effective solutions • become experienced in Python and other cutting-edge computing and mathematical tools essential for data manipulation and analysis • learn advanced techniques in machine learning to build predictive models and solve complex problems • build key skills to engage with data in areas ranging from mathematics, computer science, physics and biology to medicine, geography, development studies and economics. You'll be supported by expert faculty. Through your MSc dissertation you can focus on an area that interests you most. You could consider Data Science applications in climate change, banking, smart devices, gaming, pandemics, degenerative diseases and more. You'll graduate with the skills and knowledge for a successful career in data-driven industries such as technology, finance and engineering. You could forge a career as a data scientist, machine learning engineer or data analyst, or decide to pursue further study.

Modules

This module teaches the computer science aspects of data science. A particular focus is on how data is represented and manipulated to achieve good performance on large data sets (> 10 GBytes) where standard techniques may no longer apply. In lectures, you'll learn about data structures, algorithms, and systems, including distributed computing, databases (relational and non-relational), parallel computing, and cloud computing. In laboratory sessions, you'll develop your Python programming skills, work with a variety of data sets including large data sets from real world applications, and investigate the impact on run-time of your algorithmic choices.

Tuition fees

UK fees
Course fees for UK students

For this course (per year)

£13,225

International fees
Course fees for EU and international students

For this course (per year)

£27,100

Entry requirements

You should normally have an upper second-class (2.1) undergraduate honours degree or above. Subject-specific requirements: Your qualification should be in physics, engineering, science, computing, mathematics or life sciences. You may also be considered for the course if you have other professional qualifications or experience of equivalent standing.