MSc Data Science
Why choose this course?
Data Science is one of the most rapidly expanding areas of employment globally, due to rapid and ongoing developments in computer systems and data gathering. Large data sets are widespread in business, science and government. This course builds on the established strengths of the Mathematics and Computer Science programmes and develops a multidisciplinary approach to the computational analysis of data. Contemporary society faces new challenges in the analysis of data, predictive analytics in support of decision making processes that are both mathematical and computational. There is an increasing demand for data-savvy professionals both in industry and in research who are able make sense of large amounts of data and apply it to the solution of relevant problems. This course offers postgraduates with some background in computing, mathematics, or data-based investigation the opportunity to develop their skills in a way which will prepare them for careers in this fast-growing and exciting area which spans virtually all areas of commerce and industry as well as scientific research, and involves working with individuals and organisations to extract value from the ever-increasing volume of data that is available.
What you will study
The multidisciplinary nature of data science is reflected in this MSc programme through the careful combination of modules in data management, analysis, modelling, visualisation and artificial intelligence (AI), which are taught by a cross-disciplinary team whose expertise encompasses mathematics, statistics, AI and machine learning, information management, and user experience design. For a student to go on placement they are required to pass every module first time with no reassessments. It is the responsibility of individual students to find a suitable paid placement. Students will be supported by our dedicated placement team in securing this opportunity.
Teaching and assessment
The learning, teaching and assessment strategies reflect the programme aims and learning outcomes, student background, potential employer requirements, and the need to develop a broad range of technical skills with the ability to apply them appropriately. The use of coursework emphasises more authentic assessments, which could be, for example, from business or research contacts in local SMEs or colleagues working with "big data" in the NHS, with appropriate ethical and IP approval, as necessary. For example, students will typically create applications, documentation and visualisations, writing reports and giving presentations. Students will have the opportunity in some assignments to identify topics and target audiences in consultation with teaching staff which allows them to express their individuality and appreciate the diversity within course. In this way, as they progress through the course, students are guided and supported to assemble a portfolio of tangible outputs which evidence, explicitly, the knowledge and skills they have gained and which may be used to demonstrate their capabilities to future employers in a format that can be influenced by the students' own preferences.
After you graduate
The new Data Science course is aimed at careers contained within the more generic 'Data Science' umbrella, including Data Engineer, Data Analyst and Machine Learning Engineer.
Why choose this course?
Data Science is one of the most rapidly expanding areas of employment globally, due to rapid and ongoing developments in computer systems and data gathering. Large data sets are widespread in business, science and government. This course builds on the established strengths of the Mathematics and Computer Science programmes and develops a multidisciplinary approach to the computational analysis of data. Contemporary society faces new challenges in the analysis of data, predictive analytics in support of decision making processes that are both mathematical and computational. There is an increasing demand for data-savvy professionals both in industry and in research who are able make sense of large amounts of data and apply it to the solution of relevant problems. This course offers postgraduates with some background in computing, mathematics, or data-based investigation the opportunity to develop their skills in a way which will prepare them for careers in this fast-growing and exciting area which spans virtually all areas of commerce and industry as well as scientific research, and involves working with individuals and organisations to extract value from the ever-increasing volume of data that is available.
What you will study
The multidisciplinary nature of data science is reflected in this MSc programme through the careful combination of modules in data management, analysis, modelling, visualisation and artificial intelligence (AI), which are taught by a cross-disciplinary team whose expertise encompasses mathematics, statistics, AI and machine learning, information management, and user experience design. For a student to go on placement they are required to pass every module first time with no reassessments. It is the responsibility of individual students to find a suitable paid placement. Students will be supported by our dedicated placement team in securing this opportunity.
Teaching and assessment
The learning, teaching and assessment strategies reflect the programme aims and learning outcomes, student background, potential employer requirements, and the need to develop a broad range of technical skills with the ability to apply them appropriately. The use of coursework emphasises more authentic assessments, which could be, for example, from business or research contacts in local SMEs or colleagues working with "big data" in the NHS, with appropriate ethical and IP approval, as necessary. For example, students will typically create applications, documentation and visualisations, writing reports and giving presentations. Students will have the opportunity in some assignments to identify topics and target audiences in consultation with teaching staff which allows them to express their individuality and appreciate the diversity within course. In this way, as they progress through the course, students are guided and supported to assemble a portfolio of tangible outputs which evidence, explicitly, the knowledge and skills they have gained and which may be used to demonstrate their capabilities to future employers in a format that can be influenced by the students' own preferences.
After you graduate
The new Data Science course is aimed at careers contained within the more generic 'Data Science' umbrella, including Data Engineer, Data Analyst and Machine Learning Engineer.
