Have you ever wanted to ‘Mung’ data? Apply Machine Learning techniques? Search for hidden patterns? Be part of Big Data?
This course is your opportunity to specialize as a Data Scientist, one of the most in demand roles across all sectors including health, retail, and energy. Companies such as Google and Microsoft, and also public organisations such as the NHS are struggling to fill their vacancies in this field due to a lack of suitably qualified people. This course is unique in the UK in that it has been developed as a MSc conversion course – if you have a good honours degree in any discipline with a demonstrable mathematical aptitude, an enquiring mind, a practical and analytical approach to problem solving, and an ambition for a career in data science; then this course is for you.
During your time with us, you will develop an awareness of the latest developments in the fields of Data Science and Big Data including advanced databases, data mining and big data tools such as Hadoop. You will also gain substantial knowledge and skills with the SAS business intelligence software suite due to the partnership of the University with the SAS Student Academy.
"We are especially pleased to endorse the new MSc in Data Science. With the explosion of interest and investment in data science teams, our customers cannot get enough graduates with SAS-based analytical skills. Courses such as this new MSc are an important step forward by the University to addressing this skills shortage, especially amongst home students." - SAS
This course covers a very comprehensive range of topics split in to four large modules worth 30 credits each plus the MSc Project worth 60 credits. External speakers from blue-chip and local companies will give seminars to complement your learning, that will be real-world case studies related to the subjects you are studying in your modules. These are designed to improve the breadth of your learning and could lead to ideas that you can develop for your MSc Project.
The course is focused around the underpinning knowledge and practical skills needed for employment within the data sciences industry. There will be 22 hours of lectures; 11 hours of tutorials and 22 hours workshops; 2 hours of examination-based assessment; and 245 hours of independent study, assessed coursework and preparation for examination. This makes a total of 300 hours total learning experience.
A recent report by e-Skills and SAS (Big Data Analytics: An assessment of the demand for labour and skills, 2012-1017) indicates the demand forecast for staff with big data skills is predicted to ”rise by 92% between 2012 and 2017, and by 2017 there will be at least 28,000 job openings for big data staff in the UK each year…”
With this qualification, you’ll be equipped with the skill set and technical knowledge relevant for the data science and big data job market.
The Informatics Research Centre in the School of Computing, Science and Engineering at the University of Salford builds on the history, success and achievements of the research in Computer Science and Information Systems developed at the University of Salford over the last thirty years.
Evolving around Data and Information in all their types and usages, the Centre covers all phases and processes from data pre-processing to engineering and visualisation. The Centre is developing novel methods and systems for the analysis and recognition of various data sets, learning behaviours and causal models. The techniques and systems developed have a wide range of potential applications including digitisation of historical documents, medical diagnosis, semantic tagging, segmentation of types of viewers and their behaviours, text mining and retrieval and data visualisation.
Forensic computing, digital investigation and Cyber security is another area of expertise supported by the centre both at the theoretical and application levels.
Many students go on to further research in the fields of:
Facilities include a new Dell Cloud Computing platform with OpenStack and lab workstations, providing access to software platforms and languages specialized in Machine Learning, Data Mining, Statistical Analysis and Big Data including:
Computer science drives the fundamental technologies of today’s connected world. Suited to candidates with significant programming experience, this umbrella programme covers the foundations of a range of specialisms as well as providing the opportunity to deepen your understanding of one or more of these areas through a range of optional modules.
Semester one: Computer Vision; Designing Usable and Accessible Technologies; Evolution of Complexity; Foundations of Artificial Intelligence; Foundations of Cyber Security; Foundations of Data Science; Foundations of Web Science; Implementing Cyber Security; Intelligent Agents; Machine Learning; Robotic Systems; Software Engineering and Cyber Security; Software Modelling Tools and Techniques for Critical Systems; Software Project Management and Development; Topics in Computer Science; Web Development.
Semester two: Advanced Computer Networks; Advanced Computer Vision; Mobile Applications Development; Advanced Databases; Advanced Intelligent Agents; Advanced Machine Learning; Automated Code Generation; Automated Software Verification; Biological Inspired Robotics; Biometrics; Computational Biology; Computational Finance; Cryptography; Data Mining; Data Visualisation; E-Business Strategy; Further Web Science; Game Design and Development; Image Processing; Open Data Innovation; Secure Systems; Semantic Web Technologies; Simulation Modelling for Computer Science; The Science of Online Social Networks.
Plus three-month independent research project culminating in a dissertation.
This Master will train you to become an expert in the development and up-front professional use of computer and software systems. Nowadays, these systems are indispensable in nearly all areas of our society: in industry, the public sector, health and many social applications for end users. They are also the most complex systems ever created by humans.
The programme will teach you to specify, design, implement, test and maintain advanced software systems. It will teach you how to handle complexity and how to deal with diverse requirements such as functionality, reliability, user friendliness, security, reliability, intelligence, efficiency and cost.
You will acquire all the necessary skills to tackle complex research questions, formulate your own research goals, and successfully achieve them.
You will be trained in communication skills and stimulated to acquire a broad societal view on the relevance of computer science and technology today.
The programme is structured around a mandatory core (42 credits) of which 18 credits are dependent on the Bachelor’s track followed by the incoming student. This core focuses heavily on software development, and is the main foundation of the programme.
You can choose between two advanced specialization areas: software security or artificial intelligence. In both specializations, you will conduct your own research and develop novel technology, guided by top-experts in the international research community.
The Master’s thesis covers 24 credits, and is started at the beginning of the second stage.
General education courses (12-14 credits) cover a wide variety of topics such as advanced language courses, economy, law, advanced mathematic courses. All students have the additional option to complete their programme with any course offered by the university (6 credits).
At the Faculty of Engineering Science, students are given the opportunity to complete one or two semesters of their degree within the Erasmus+ programme at a European university, or a university outside Europe.
Students are also encouraged to carry out industrial and research internships abroad under supervision of the departmental Internship Coordinator. These internships take place between the third Bachelor’s year and the first Master’s year, or between the two Master’s years.
Other study abroad opportunities are short summer courses organised by the Board of European Students of Technology (BEST) network or by universities all over the world.
The Faculty of Engineering Science is also member of the international networks CESAER, CLUSTER and ATHENS, offering international opportunities as well.
More information on the international opportunities at the faculty is available on the website.
The programme, courses, and areas of specialisation are strongly linked to the research groups. This guarantees a state-of-the-art education in the field of computer science. Research activities (e.g. Master’s thesis) also form part of a student’s curricula.
A significant number of courses are focused on industry-relevant skills and content. The amount of industry-related research projects in the department of computer science allows us to include relevant content in our courses.
The 2015 student survey indicated that the following aspects of our programme score very high: structure of the programme, electives, theoretical foundations, research & scientific content, quality of teaching staff, overall logistics.
This is an initial Master's programme and can be followed on a full-time or part-time basis.
Software engineers can be found in nearly all sectors of society. Software is a crucial component in all industrial processes, in the service and entertainment industry, and in our society as a whole. Masters of Computer Science are active in the software-development industry as well as in telecommunication and other industries. Many of our graduates work in hospitals, in the banking sector, in social organisations, and for the government as heads of ICT.