Master the art of data visualisation. Students will be empowered with the practical skills and insights needed to succeed in data visualisation for impactful communication. Through hands-on learning, participants will perfect the skill of selecting the right chart types, crafting visually compelling data representations, and navigating common pitfalls with finesse.
An introduction to data-driven decision-making. Develops skills in using data analysis methods and tools for analysing information. Equips students to apply modelling skills in a variety of decision-making applications relevant to business.
Rapid advancements in computing power and data storage capacity has changed how digital data is created, stored, consumed, and managed. As a result, business data exists in many formats and representations. Students will be equipped with contemporary data management tools and exploratory techniques to realise the value of data as a business asset.
Organisations are increasingly adopting big data analysis, predictive analytics, social data mining, and deep machine learning to gain business intelligence and insight. The value of such technologies relies on having high-quality data, yet raw data is messy and its transformation to add value is often neglected. Students will explore a data wrangling toolbox to add value to data.
Provides essential skills required to obtain data-driven insights that augment business decisions across a variety of application areas. This involves the identification of the problem, and implementation of effective data visualisations and appropriate machine learning models using cloud-based data analytics tools. Key concepts around big data will also be introduced.
Uncertainty exists in all management decisions and simulation is used for analysing systems in industry. Focuses on modelling real-world problems using a commercial simulation tool and the application of skills through industrial case studies. Topics include the simulation process, general queue modelling, modelling networks (computer or transportation networks) and simulating operations (machine scheduling or assembly line modelling).
Focuses on the design and development of end-to-end analytics solutions to business problems. Engages students in issues and challenges relating to problem definition, selection of data analytics tools and techniques, and strategies for ensuring the effective communication of data insights to stakeholders. Develops strategic mindset and teamwork skills.