Program start date | Application deadline |
2025-10-01 | - |
Program Overview
The MEng Computing program at Imperial College London provides a comprehensive education in the fundamentals of computer science. It emphasizes sound principles, logical thinking, and the ability to build and adapt complex systems. Through a range of core and optional modules, students gain expertise in areas such as software engineering, computer architecture, and machine learning. The program culminates in an individual project, industrial placement, and specialized coursework in the final year, preparing graduates for successful careers in computing and technology.
Program Outline
Degree Overview:
Computing is a creative and wide-ranging subject that focuses on using sound underlying principles and logical thinking to design and build systems that really work.
- Develop technical expertise in designing and building systems using sound underlying principles and logical thinking.
- Develop a strong background in discrete mathematics (logic, sets, relations and grammars) – the basic mathematics of computing – along with classical mathematics and statistics relevant to applications engineering and management.
- Gain valuable skills and experience through an industrial placement at the end of the third year.
- Achieve Master's level study in the final year, with a wide choice of optional modules and a substantial individual project on a subject of your choice.
Outline:
Year 1:
- Core Modules:
- Introduction to Computer Systems
- Introduction to Databases
- Introduction to Computer Architecture
- Computing Practical 1
- Discrete Mathematics, Logic and Reasoning
- Graphs and Algorithms
- Calculus
- Linear Algebra
Year 2:
- Core Modules:
- Algorithm Design and Analysis
- Software Engineering Design
- Models of Computation
- Operating Systems
- Networks and Communications
- Compilers
- Probability and Statistics
- Computing Practical 2
- Computing Group Project
- Optional Modules:
- Symbolic Reasoning
- Computational Techniques
Year 3:
- Core Modules:
- Industrial Placement (First Part)
- I-Explore (This module offers choices from a range of subjects hosted outside of the department, including business, management, and more.)
- Optional Modules:
- The Theory and Practice of Concurrent Programming
- Computer Vision
- Graphics
- Custom Computing
- Communicating Computer Science in Schools
- Network and Web Security
- Advanced Computer Architecture
- Robotics
- Networked Systems
- System Performance Engineering
- Operations Research
- Distributed Algorithms
- Type Systems for Programming Languages
- Data Processing Systems
- Introduction to Machine Learning
- Technical Option (outside Department of Computing)
- Software Engineering Group Projects
Year 4:
- Core Modules:
- Industrial Placement (Second Part)
- Individual Project
- Optional Modules - Group A:
- Scalable Software Verification
- Scalable Systems and Data
- Privacy Engineering
- Cryptography Engineering
- Advanced Computer Graphics
- Computational Finance
- Complexity
- Software Reliability
- Advanced Computer Security
- Deep Learning
- Machine Learning for Imaging
- Principles of Distributed Ledgers
- Program Analysis
- Quantum Computing
- Software Engineering for Industry
- Computational Optimisation
- Natural Language Processing
- Mathematics for Machine Learning
- Reinforcement Learning
- Modal Logic for Strategic Reasoning in AI
- Advanced Computer Architecture
- Custom Computing
- Robot Learning
- Scheduling and Resource Allocation
- Methods and Tools in the Theory of Computing
- Computational Neurodynamics
- Human-Robot Interaction
- Statistical Information Theory
- Deep Graph-based Learning
- Optional Modules - Group B:
- Communicating Computer Science in Schools
- Elective(s) from outside the Department of Computing
Assessment:
Year 1:
- 10% Coursework
- 84% Examinations
- 6% Practical
Year 2:
- 10% Coursework
- 57% Examinations
- 33% Practical
Year 3:
- 8% Coursework
- 42% Examinations
- 50% Practical
Year 4:
- 9% Coursework
- 50% Examinations
- 41% Practical
Assessment Methods:
- Programming exercises
- Computer-based programming tests
- Written coursework
- Computer-based coursework
- Examinations
- Software demonstrations
- Group work
- Written reports
- Research summaries
- Oral presentations
Teaching:
Teaching and Learning Methods:
- Lectures
- Tutorials
- Laboratory-based teaching
- In-class problem solving
- Personal supervision of project work
Balance of Teaching and Learning:
- Years 1 and 2: 20% Lectures and tutorials, 5% Laboratory sessions, 75% Independent study
Careers:
- 96% of Imperial Computing graduates are in work or further study.
- 90% of Imperial Computing graduates are in highly skilled work or further study.
- Potential career paths include:
- Management consultancy
- Corporations
- Computer gaming and special effects
- Banking and finance
- Gain transferable skills relevant to a career in industry and academia.
- Specialized knowledge makes graduates highly sought after in a range of sectors.
Other:
- The Industrial Placement does not contribute to your final degree classification.
- Transfers from Computing to Joint Mathematics and Computing courses are normally not possible and are dealt with on a case by case basis.
- If you wish to progress onto one of the MEng programmes in Year 3, you must achieve an overall average of 60% in your second year.
- Transfer between the BEng in Mathematics and Computer Science and MEng in Mathematics and Computer Science is possible until the end of Year 2 subject to meeting certain minimum results criteria.
- Normally only students who are on track for at least a 2:1 will be eligible for placements in France and Germany. Only students on track to achieve a 1st will be eligible for placements in the USA.
- The list of universities located abroad that the Department currently has partnerships with is illustrative. Partnerships with universities are subject to continuous review and individual partnerships may or may not be renewed.