Train to become a data analyst in a growing industry by studying techniques such as data mining, statistical modelling, business intelligence and data visualisation. Study on a course which has been developed with direct input from industry experts who will bring real life business case scenarios to you.
More about this course
This specialist advanced course will equip students with the theoretical, technical and practical data analytics competencies required in an area of economic growth. The course curriculum content has been developed with direct input from industry experts and utilises specialist software tools and techniques. Students’ experience of the course will be enriched with exposure to real life business case scenarios brought to them by skilled professionals in industry.
The specialist nature of the course will allow students to explore and experience advanced techniques in data science. Students will acquire practical skills, often first-hand from an external practitioners, preparing them for employment as data analysts. Students will also be trained in the use of software tools and environments currently used by the industry sector. For example, students on this course will have exposure to R and Python programming, IBM SPSS, SAS®, Tableau, Oracle and Hadoop.
A range of assessment methods are used on the course, including written reports, practical and research assignments, demonstrations, presentations, group work and examinations.
The modules listed below are for the academic year 2016/17 and represent the course modules at this time. Modules and module details (including, but not limited to, location and time) are subject to change over time.
Year 1 modules include: -Data Analysis and Visualization (core, 20 credits) -Data Mining for Business Intelligence (core, 20 credits) -Data Modelling and OLAP Techniques for Data Analytics (core, 20 credits) -MSc Project (core, 60 credits) -Programming for Data Analytics (core, 20 credits) -Statistical Modelling and Forecasting (core, 20 credits) -Financial Mathematics (option, 20 credits) -Work Related Learning (option, 20 credits)
After the course
On completion of the course graduates will be well equipped to work in some of the fastest growing sectors of the data science and big data industries. The course offers wide-ranging career opportunities in the commercial industry, public and financial services, especially in areas requiring big data analysis such as consumer, healthcare, scientific, financial, security intelligence, business and social sciences.
Job roles include data scientist, data analyst, digital analyst, big data consultant, statistical analyst and data modeller. Graduates will be eligible to work as data analysts or data scientists in a multitude of areas where skills such as R or Python programming, machine learning and statistical modelling, SAS® and SPSS experience, data visualisation and data-driven decision-making are required.
The course also provides an excellent basis for further study for those wishing to pursue a higher-level research degree or embark on an industry-based research career.