Data is a vital asset valued by virtually every organisation in the world. It provides the basis for sensible, evidence-based decision making, and the ability to manage and make sense of data is a key skill in the modern workplace. In the last decade, streams of data of various types have grown in volume and velocity such that they require specialist skills in order to get the most value from them. Data scientists are responsible for building intelligent systems, mastering intuitive processes and bringing structure to the vast quantities of data to unlock the potential for improvement and competitive advantage.

The Graduate Certificate in Data Science will provide students with the required knowledge and practical skills to analyse and manage data. This course will prepare students to solve complex and challenging problems.

The Graduate Certificate in Data Science is a course that complements existing skill sets and provides opportunity to up-skill for positions that have a rigorous quantitative aspect.

Course Aims

The Graduate Certificate in Data Science is designed for students with a Bachelor degree in a relevant discipline who are seeking to enhance their skills in the analysis and management of large data. The aim of the course is to enable students to enhance their competencies in a range of areas critical to data science and the course will equip graduates with the knowledge and skills required to pursue a range of analytical and data science related career paths or articulate into further studies in the area of data science.

Learning Outcomes

Upon completion of this course, students will be able to:

• understand the key tools, methods and theories used to data science to an advanced level of depth and sophistication;
• synthesise information from data and understand the lifecycle of data within an organisation;
• apply problem solving skills and specialist knowledge in statistics and software development to implement data analysis solutions for real-world problems;
• communicate effectively with expert and non-expert audiences to understand issues and gather requirements for the development of data analysis strategies and related systems within an organisation;
• evaluate information from a range of sources, such as peer-reviewed literature and technical documentation, to understand current developments in the area of data science; and
• understand and communicate the ethical and legal issues that relate to the practice of data science.