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Artificial Intelligence MSci

UCAS code: G703

Key information

Course type:
Single honours
Delivery mode:
Campus
Study mode:
Full time
Required A-level:
A*A*A
Full entry requirements, including contextual requirements
Duration:
4 years
Application status:
Open
Start date:
September 2025
Application deadline:
31 January 2024
Apply via UCAS

AI significantly affects people’s lives, and it is encountered in more and more of our daily activities. These include activities such as using smart devices, digital voice assistants, and travel aids, as well as banking online or receiving personalised recommendations about movies to rent. Meanwhile, AI is increasingly reliant on leveraging the widespread availability of (often very large) datasets that encode relationships between data inputs to decision making processes, and the outcome of these processes, so that AI applications can enhance human decision making in a wide variety of everyday tasks (e.g. recommender systems) and specialised tasks (e.g., deciding on legal litigation risks, decisions in business/logistics planning, or decisions based on interpretation of visual data such as diagnostic scans in medicine), as well as AI applications that autonomously make and implement decisions (e.g., robots that need to sense their environment and plan actions). These applications require expertise in a broad range of Artificial Intelligence areas. The MSci in Artificial Intelligence will allow you to understand the underlying principles of these areas, including: - Foundations of AI (e.g. programming, discrete mathematics, algorithm design) - Data Science and Machine Learning (e.g. natural language processing, human-AI interaction) - Knowledge Representation, Reasoning, and Interactions (e.g. data visualisation, knowledge engineering, formal verification) - Optimisation, Planning and Autonomous Agents (e.g. autonomous robot programming, logic, network optimisation) - Ethics and philosophy of AI (e.g., legal, social, ethical and professional issues in AI and in robotics system development, philosophical work on the impact and on dangers of AI) - AI Engineering (e.g. internet and web systems, cloud-based services, AI security and privacy) It will also provide you with the background knowledge and skills required to become a successful AI professional able to work in a range of exciting roles ranging from big data engineer to robotics engineer. Women in Science As part of the faculty's work on diversity & inclusion, we are actively working to support women in science, technology, engineering and mathematics in order to address the current imbalance of women working and studying in these areas. Read more about the Women in Science Initiative here: https://www.kcl.ac.uk/nmes/women-in-science.

Key benefits

  • 6th in the UK for Computer Science (QS World Rankings by subject 2024)
  • You'll interact with world-class experts in many exciting areas of AI, including Safe and Trusted AI, Trusted Autonomous Systems, Distributed AI, and Reasoning and Planning.
  • You'll study a wide-range of innovative modules, covering both the theory and practice of modern AI.
  • Our central London location is close to top, global AI companies, such as Google and Amazon, and gives unparalleled access to leading scientific societies, including the Chartered Institute for IT (BCS) and the Institution of Engineering and Technology (IET).
  • This degree has been accredited by BCS, The Chartered Institute for IT. Accreditation is a mark of assurance that the degree meets the standards set by BCS. An accredited degree entitles you to professional membership of BCS, which is an important part of the criteria for achieving Chartered IT Professional (CITP) status through the Institute. Some employers recruit preferentially from accredited degrees, and an accredited degree is likely to be recognised by other countries that are signatories to international accords
  • 7th in the UK for employability (Times Higher Education Graduate Employability rankings 2023/4)

Employability

There is a widening demand and supply gap for AI skills, with a significant increase in online AI and Data Science vacancies. Many firms that have vacancies for AI roles had at least one vacancy that was difficult to fill. An AI professional needs to exploit a broad range of skills and is likely to conduct their work according to a range of both well-established and cutting-edge roles.

Examples of such roles are data scientist, including big data engineer, legal data scientist, and business data scientist, cloud AI engineer, logistic engineer, negotiation engineer, knowledge/graph engineer, robotics engineer, information retrieval and natural language processing applied scientist, as well as algorithmic impact and responsibility scientist.

In such roles, an AI professional may manage and analyse data of different types using a range of technologies, or extract knowledge of different forms from the data. In addition, they may develop advanced control and coordination mechanisms for robots, or understand the ethical impacts of AI, mitigating risks and ethical harms arising from the deployment of AI. 

Destinations

Recent graduates have found employment within the following job roles and companies:

  • Data Scientist
  • Cloud AI Engineer
  • Logistic Engineer
  • Negotiation Engineer
  • Knowledge/Graph Engineer
  • Robotic Engineer
  • Information retrieval and natural language processing applied Scientist
  • Algorithmic impact and responsibility Scientist

Employability

There is a widening demand and supply gap for AI skills, with a significant increase in online AI and Data Science vacancies. Many firms that have vacancies for AI roles had at least one vacancy that was difficult to fill. An AI professional needs to exploit a broad range of skills and is likely to conduct their work according to a range of both well-established and cutting-edge roles.

Examples of such roles are data scientist, including big data engineer, legal data scientist, and business data scientist, cloud AI engineer, logistic engineer, negotiation engineer, knowledge/graph engineer, robotics engineer, information retrieval and natural language processing applied scientist, as well as algorithmic impact and responsibility scientist.

In such roles, an AI professional may manage and analyse data of different types using a range of technologies, or extract knowledge of different forms from the data. In addition, they may develop advanced control and coordination mechanisms for robots, or understand the ethical impacts of AI, mitigating risks and ethical harms arising from the deployment of AI. 

Destinations

Recent graduates have found employment within the following job roles and companies:

  • Data Scientist
  • Cloud AI Engineer
  • Logistic Engineer
  • Negotiation Engineer
  • Knowledge/Graph Engineer
  • Robotic Engineer
  • Information retrieval and natural language processing applied Scientist
  • Algorithmic impact and responsibility Scientist

Key information

Course type:
Single honours
Delivery mode:
Campus
Study mode:
Full time
Required A-level:
A*A*A
Full entry requirements, including contextual requirements
Duration:
4 years
Application status:
Open
Start date:
September 2025
Application deadline:
31 January 2024
Apply via UCAS

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