Data Science and Analytics MSc

Course summary

This course (previously Business Intelligence and Analytics MSc) addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. The course stretches the artificial intelligence (AI), machine learning (ML) and decision science themes to business intelligence, data science and business analytics.

You'll focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, using applications and case studies, while gaining a deep appreciation of the underlying models and techniques. You'll also gain a greater understanding of the impact technological advances have on nature and practices adopted within data science, business intelligence and analytics, and how to adapt to these changes.

Embedded into the course are two key themes. The first will help you to develop your skills in the use and application of various technologies, architectures, techniques, tools, and methods for data science. These include data warehousing and mining, distributed data management, and the technologies, architectures, and appropriate AI and ML techniques. The second theme will enhance your knowledge of algorithms and the quantitative techniques including AI, ML, and Operational Research (OR) suitable for analysing and mining data and developing decision models in a broad range of application areas. The project consolidates the taught subjects covered, while giving you the opportunity to pursue in-depth study in your chosen area.

Teaching approaches include lectures, tutorials, seminars, and practical sessions. You will also learn through extensive coursework, class presentations, group research work, and the use of a range of industry-standard software such as R, Python, Simul8, Palisade Decision Tools, Tableau, and Oracle.

Modules are typically assessed through practical coursework, which may also include an in-class test.

Top reasons to study with us

• Master key data science and analytics skills – You’ll develop your skills in the use and application of various technologies, architectures, techniques, tools, and methods, including data warehousing and mining, distributed data management, and appropriate AI and ML techniques
• Develop your problem-solving skills – You’ll focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, and gain a deep appreciation of the underlying models and techniques
• Gain industry-insider knowledge – You’ll attend presentations from industry professionals and have the opportunity to go on site visits to see the work of data science and analytics teams
• Get access to the essential software and languages – You’ll use a range of industry-standard software such as R, Python, SQL, Simul8, Palisade Decision Tools, Tableau, and Oracle
• You'll enhance your knowledge of algorithms and quantitative techniques including Al, ML, Operational Research (OR), and Advanced Analytics suitable for analysing and mining data and developing decision models in a broad range of application areas

You'll focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, and gain a deep appreciation of the underlying models and techniques, equipping you with the practical skills needed to become a data science and analytics specialist.

Typically, graduates of this course will be employed as consultants, data scientists, decision modelling or advanced data analysts, members of technical/analytics teams supporting the decision making of middle and top management in a diverse range of sectors.

With a growing global network of 3,000 employers, our Careers and Employability Service is here to support you to achieve your full potential.

This course will prepare you for roles such as:

• Ad Technology Manager
• Big data architect
• Chief data officer
• Data analyst
• Data scientist
• Enterprise data architect
• Insights manager
• Lead information analyst
• Managing consultant
• Revenue optimisation manager
• Senior data scientist
• Senior insight analyst
• Technical insight analyst