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MSc in Data Science aims to equip students with a solid grounding in data science concepts and technologies for extracting information and constructing knowledge from data. Students of the MSc Data Science will study the computational principles, methods, and systems for a variety of real world applications that require mathematical foundations, programming skills, critical thinking, and ingenuity. Development of research skills will be an essential element of the Data Science programme so that students can bring a critical perspective to current data science discipline and apply this to future developments in a rapidly changing technological environment.
The MSc Data Science programme focuses on three core technical themes: data mining, machine learning, and visualisation. Data mining is fundamental to data science and the students will learn how to mine both structured data and unstructured data. Students will gain practical data mining experience and will gain a systematic understanding of the fundamental concepts of analysing complex and heterogeneous data. They will be able to manipulate large heterogeneous datasets, from storage to processing, be able to extract information from large datasets, gain experience of data mining algorithms and techniques, and be able to apply them in real world applications. Machine learning has proven to be an effective and exciting technology for data and it is of high value when it comes to employment. Students of the Data Science programme will learn the fundamentals of both conventional and state-of-the-art machine learning techniques, be able to apply the methods and techniques to synthesise solutions using machine learning, and will have the necessary practical skills to apply their understanding to big data problems. We will train students to explore a variety visualisation concepts and techniques for data analysis. Students will be able to apply important concepts in data visualisation, information visualisation, and visual analytics to support data process and knowledge discovery. The students of the Data Science programme also learn important mathematical concepts and methods required by a data scientist. A specifically designed module that is accessible to students with different background will cover the basics of algebra, optimisation techniques, statistics, and so on. More advanced mathematical concepts are integrated in individual modules where necessary.
The MSc Data Science programme delivers the practical components using a number of programming languages and software packages, such as Hadoop, Python, Matlab, C++, OpenGL, OpenCV, and Spark. Students will also be exposed to a range of closely related subject areas, including pattern recognition, high performance computing, GPU processing, computer vision, human computer interaction, and software validation and verification. The delivery of both core and optional modules leverage on the research strength and capacity in the department. The modules are delivered by lecturers who are actively engaged in world leading researches in this field. Students of the Data Science programme will benefit from state-of-the-art materials and contents, and will work on individual degree projects that can be research-led or application driven.
Modules for the MSc Data Science programme include:
- Visual Analytics
- Data Science Research Methods and Seminars
- Big Data and Data Mining
- Big Data and Machine Learning
- Mathematical Skills for Data Scientists
- Data Visualization
- Human Computer Interaction
- High Performance Computing in C/C++
- Graphics Processor Programming
- Computer Vision and Pattern Recognition
- Modelling and Verification Techniques
- Operating Systems and Architectures
The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, our Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.
As part of the expansion of the Department of Computer Science, we are building the Computational Foundry on our Bay Campus for computer science and mathematical science.
- Data Analyst
- Data mining Developer
- Machine Learning Developer
- Visual Analytics Developer
- Visualisation Developer
- Visual Computing Software Developer
- Database Developer
- Data Science Researcher
- Computer Vision Developer
- Medical Computing Developer
- Informatics Developer
- Software Engineer
This programme will allow you to explore the philosophical themes and ideas that lie behind modern science.
You’ll discuss a range of issues that animate debates in contemporary philosophy of science, gaining an insight into how we understand science and how this has changed over time. You’ll think about the nature and extent of scientific knowledge and explanation, for example, as well as specialising in topics that suit your interests, from the metaphysics of science to epistemological topics such as realism and representation.
Our core module will introduce you to concepts and trends in philosophy of science, while you’ll select optional modules on topics of your choice. You could even broaden your approach by taking a module in Analytic Philosophy or the history of modern science communication, or gain more research experience by extending your dissertation.
Guided by internationally renowned researchers in our Centre for History and Philosophy of Science, you’ll learn in a supportive and stimulating environment.
We have world-class research resources to support your studies. In addition to its collections in history and philosophy, the Brotherton Library houses extensive manuscript, archive and printed material in its Special Collections, including Newton’s Principia, a first edition of his Opticks and thousands of books and journals on topics in the history of science. The Edward Boyle Library also possesses an extensive collection of works in the philosophy of science and across the full range of scientific topics in general.
The Centre also hosts a number of research seminars given by visiting speakers, staff members and doctoral students and which all postgraduate students are encouraged to attend. There are also regular reading groups on a wide range of topics and the seminar series of other centres within the School are also available.
From the start of the programme you’ll explore issues and concepts in philosophy of science, as a core module introduces you to classic debates and recent trends in the subject. You’ll then build on this knowledge when you choose from a range of optional modules throughout the year, allowing you to specialise in areas such as the philosophy of physics, philosophy of biology, or realism and representation in science.
Throughout the year, you’ll gain a firm foundation in philosophy of science as well as in-depth knowledge of specialist topics. You’ll take this a step further with your dissertation, an independently researched piece of work on a topic of your choice that gives you the chance to showcase your skills.
If you want to go into greater depth, you have the choice to extend your dissertation. Alternatively, you can select another module on a topic such as modern science communication or analytic philosophy, putting your research into a broader context.
If you choose to study part-time, you’ll study over a longer period and take fewer modules in each year.
You’ll take two compulsory modules, though you can choose whether to take a standard (60 credits) or extended (90 credits) dissertation. You’ll then choose one or two optional modules.
Most of our taught modules combine seminars and tutorials, where you will discuss issues and concepts stemming from your reading with a small group of students and your tutor. You’ll also benefit from one-to-one supervision while you complete your dissertation. Independent study is also an important element of the programme, allowing you to develop your skills and pursue your own interests more closely.
We assess your progress using a combination of exams and coursework, giving you the freedom to research and write on topic areas that suit your interests within each module you study.
The subject knowledge you’ll gain from this programme, as well as the advanced skills in research, analysis and communication, will open doors to a wide range of careers.
This programme is good preparation for fields such as public engagement with science, but graduates from our School have pursued diverse careers in fields such as teaching, consultancy, business management, administration, accountancy and the civil service among others. Many of our graduates also go onto further study at PhD level and continue to work in academia.
We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.
The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.