IS-427 Data Science Applications II

Upon completion of the course, students should:

• have knowledge about statistical concepts such as probability and modeling and how to apply them in practice
• be able to promote data-analytic thinking and explain how to extract knowledge from different types of big data
• be able to identify the potential for creating business and societal value out of big data
• be able to discuss why and how the change in the digital era and data availability can transform business and society
• have thorough knowledge of how big data and analytics can foster successful digital transformations
• be able to use advanced business intelligence platforms, including data visualisation, communication, forecasting, and prediction
• be able to run machine learning algorithms in a no-coding environment and interpret the results
• understand the role of data, information, and data analytics in managerial decision making
• be able to evaluate and assess business problems, propose, and develop data-driven business models, strategies, and solutions
• be able to use advanced business intelligence and machine learning to organisational decision making
• have achieved a common understanding that will lead to more efficient communication between management, technical/development, and data science teams
• be able to understand the basic principles of data governance, and apply it to the lifecycle of data and information availability and presentation
• be able to understand and apply basic principles of privacy regulations, and ethical data management, ensuring responsible use of data, compliance with legal frameworks and stakeholders' interests
• be able to communicate analytical results through effective storytelling, tailoring dashboards and presentations to both technical and managerial audiences, facilitating the collaboration between management, technical/development, and data science teams