Specialism
Certification
MSc
Qualification level
MSc
Location
Manchester
Study type
Classroom
Duration
Full-time: 1 year; Part-time: 3 years
Price
Full-time - £7,560 Part-time - £1,260 per 30 credits module

About the course

Course content

IN BRIEF:

  • Study a course that is unique in the UK and has been specifically developed to meet the skills gap. Course content can be applied to very diverse fields- there are many job opportunities in this area.
  • Gain SAS certification.
  • Learn to tell a story from data. Become immersed in Big Data techniques and platforms, working with real-world messy data to gain experience across the data science stack.
  • Part-time study option
  • International students can apply

COURSE SUMMARY

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

COURSE DETAILS

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.

TEACHING

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.

  • Lectures will be used to introduce ideas, and to stimulate group discussions.
  • Tutorials will be used to develop problem solving strategies and to provide practice and feedback with scenarios to help with exam preparation.
  • Workshops will be used to develop expertise in SAS tools, by analysing example datasets of increasing complexity.

ASSESSMENT

  • 50% of the assessment will comprise a practical project where students will be given some data, will devise and carry out an analysis strategy and will present their interpretations and explain their strategy. 
  • 50% will comprise an examination, which will assess more theoretical aspects of the course and will explore students’ immediate response to unseen scenarios or data.

CAREER PROSPECTS

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.

FURTHER STUDY

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:

  • Actionable Knowledge Discovery and Semantic Web
  • Software Engineering and applications
  • Big Data, Data Mining and Analytics
  • Image and document processing and analysis
  • Cyber Security and Forensics
  • Information visualisation and virtual environments

FACILITIES

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:

  • R, SAS Enterprise Guide & Miner, Python, Apache Hadoop & Spark, RapidMiner
  • NoSQL databases ie MongoDB

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