Postgraduate programme

ARTIFICIAL INTELLIGENCE

Offered by IMPERIAL COLLEGE LONDON

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Programme overview

Why choose this programme?

Aimed at mathematically-minded STEM graduates, this Master's degree delivers intensive training in programming and the fundamentals of artificial intelligence (AI).

As well as learning the technical skills required for this growing area of computing science, you'll have the chance to explore realistic applications through group and individual projects.

This course offers you the chance to forge links with major technology companies and work within industry-initiated projects.
How will studying at Imperial help my career?

- Develop the skills needed by industries recognising AI's transformative potential.
- Find employment in a variety of sectors, from healthcare to manufacturing to the automotive industry (driverless cars).
- Computing graduates are sought after in roles such as application/web development, networking, AI, media, finance, robotics, and computer games.
- Other potential career paths include chip design, cyber security, data management, bio-medical systems and transport.

Modality

ONLINE

Entry requirements

First-Class Honours in Mathematics, Physics, Engineering or other degree with substantial Mathematics content.

Dates and duration

1 Year

SYLLABUS

Core modules

- Introduction to Machine Learning
- Python Programming
- Introduction to Symbolic Artificial Intelligence
- Ethics, Fairness, and Explanation in AI
- Software Engineering Group Project

Optional Modules

Group 1

- Computer Vision
- Reinforcement Learning
- Computational Optimisation
- Mathematics for Machine Learning
- Formal Methods for Safe AI
- Logic-Based Learning
- Deep Learning
- Probabilistic Inference
- Machine Learning for Imaging
- Natural Language Processing
- Robot Learning
- Robotics
- AI Ventures
- Computational Neurodynamics
- Deep Graph-Based Learning
- Human-Robot Interaction
- Software Engineering for Machine Learning Systems
- Non-Euclidean Methods in Machine Learning

Group 2

- Computational Finance
- Principles of Distributed Ledgers
- Quantum Computing
- Statistical Information Theory