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Utilizing Artificial Intelligence (AI) needs both business acumen and some technical knowledge on how it works. Applying AI appropriately to real life scenarios requires expertise to plan, design and implement AI solutions. There are several forms of AI with different implications for all the stakeholders involved. This module explores the main categories of AI solutions and how they can be utilised in the best way possible. The module is divided into three sections: The first section discusses how AI changes society and business models. This includes specific applications, opportunities and challenges. The second section discusses how AI influences specific relationships such as the relationship between a retailer and a customer or an employer and an employee. This includes concerns around transparency, privacy and trust. Lastly the third and final section provides an introduction of some additional AI concepts that will be covered more extensively in subsequent modules. As the strength and weaknesses of AI are understood better, the central role humans still hold emerges strongly. Student will leave the module with greater ability and confidence in how to apply AI to business. More specifically, the student will be better equipped to lead in AI adoption, and act as a bridge between their organization and technology providers.

This module introduces the fundamental concepts of machine learning and artificial intelligence. The content covers a broad range across the history of AI using computational, representational, algorithmic, and philosophical perspectives. The module looks at machine intelligence and machine learning as a fundamental attribute of artificial intelligence.

This module introduces the fundamental concepts of machine learning and artificial intelligence. The content covers a broad range across the history of AI using computational, representational, algorithmic, and philosophical perspectives. The module looks at machine intelligence and machine learning as a fundamental attribute of artificial intelligence.

The aim of the module is to expose the students to modern chemical informatics, machine learning (ML) and artificial intelligence (AI) driven approaches for computational modelling and prediction, illustrated with applications to research in to the discovery of new pharmaceuticals and materials. The module will introduce the basic techniques of applying AI and ML to chemistry and the opportunity to apply these ideas to specific examples as part of a mini-project.

The aim of the module is to expose the students to modern chemical informatics, machine learning (ML) and artificial intelligence (AI) driven approaches for computational modelling and prediction, illustrated with applications to research in to the discovery of new pharmaceuticals and materials. The module will introduce the basic techniques of applying AI and ML to chemistry and the opportunity to apply these ideas to specific examples as part of a mini-project.

The aim of the module is to expose the students to modern chemical informatics, machine learning (ML) and artificial intelligence (AI) driven approaches for computational modelling and prediction, illustrated with applications to research in to the discovery of new pharmaceuticals and materials. The module will introduce the basic techniques of applying AI and ML to chemistry and the opportunity to apply these ideas to specific examples as part of a mini-project.

The first part of the course is devoted to exploring a given topic via group work, assessed via short, written summary (extended abstract) and oral presentation.
The second part consists of an individual dissertation that is assessed via a written report.
The content and the scope of both group work and individual dissertations are based on physics and astronomy ideas with the focus on independently researching them, report writing in a style of scientific papers, presentation skills as well as effective team working.

The first part of the course is devoted to exploring a given topic via group work, assessed via short, written summary (extended abstract) and oral presentation.
The second part consists of an individual dissertation that is assessed via a written report.
The content and the scope of both group work and individual dissertations are based on physics and astronomy ideas with the focus on independently researching them, report writing in a style of scientific papers, presentation skills as well as effective team working.