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MEng Computer Science with Artificial Intelligence (with a year in industry)

University of York

Institution
University of York
Level
undergraduate
Subject
Computer Science with Artificial Intelligence (with a year in industry)
Duration
5 years
UCAS code
G4GR
Typical offer
A-level AAB, IB 37

Entry requirements

A level: A*AA including Mathematics. If you are studying towards a fourth A level, we will make an alternative offer of AAAA including Mathematics. IB: 37 points overall, including 5 in Higher Level Mathematics (either Analysis and Approaches or Applications and Interpretations), or 6 in Standard Level Mathematics (Analysis and Approaches). BTEC: DDD plus grade B in A level Mathematics (or equivalent qualification) We consider a range of BTEC qualifications equivalent to 3 A Levels, or in combination with A Levels or other qualifications. For example: Distinction, Distinction in BTEC Level 3 National Diploma plus A in A Level Mathematics Distinction in BTEC Level 3 National Extended Certificate plus AA at A level including Mathematics Distinction, Distinction in 2 BTEC Level 3 National Extended Certificates plus A in A Level Mathematics

About this course

MEng (Hons) in MEng (Hons) Computer Science with Artificial Intelligence (with a year in industry), a computer science and computer science (artificial intelligence) degree spanning computational systems, algorithms, and intelligent technologies. Core topics include Programming, Systems Design, Computer Architecture, Embedded Systems, Data Analysis, and Artificial Intelligence & Machine Learning. This five-year programme includes an integrated year in industry for paid professional experience. The first year covers fundamental principles through modules such as Software 1: Foundations of Programming for Computer Science, Theory 1: Mathematical Foundations of Computer Science, Human-Computer Interaction, and Software 2: Object-Oriented Data Structures and Algorithms. Year 2 advances into core engineering and systems with Engineering 1: Systems and Software Engineering, Systems and Devices 2: Operating Systems, Security and Networking, Theory 3: Computability, Complexity and Logic, and Intelligent Systems: Machine Learning and Optimisation. Year 4 focuses on advanced artificial intelligence via modules like Computer Science Project (Artificial Intelligence topic), AI Search and Logic, Autonomous Robots, and Deep Learning. Year 5 involves higher-level study centred on Group Project (Integrated Masters). Students can also select from various optional modules including Cryptography Theory and Practice, Embedded Systems Design and Implementation, and Quantum Computation in their later years.

Modules

  • Software 1: Foundations of Programming for Computer Science
  • Theory 1: Mathematical Foundations of Computer Science
  • Human-Computer Interaction
  • Software 2: Object-Oriented Data Structures and Algorithms
  • Systems and Devices 1: Introduction to Computer Architectures
  • Theory 2: Formal Languages and Automata
  • Engineering 1: Systems and Software Engineering
  • Systems and Devices 2: Operating Systems, Security and Networking
  • Theory 3: Computability, Complexity and Logic
  • Intelligent Systems: Machine Learning and Optimisation
  • Data: Introduction to Data Science
  • Systems and Devices 3: Advanced Computer Systems
  • Computer Science Project (Artificial Intelligence topic)
  • AI Search and Logic
  • Autonomous Robots
  • Deep Learning
  • Engineering LLM-Based Agents and Applications
  • Large Language Models
  • Natural Language Processing
  • Cryptography Theory and Practice
  • Embedded Systems Design and Implementation
  • Engineering 2: Automated Software Engineering
  • Ethical Hacking, Analysis and Investigation
  • High-Integrity Systems Engineering
  • High-Performance Parallel and Distributed Systems
  • Human Factors: Technology in Context
  • Legal Practice, Technology and Computer Science
  • Network Security
  • Player Experiences in Digital Games
  • Qualitative Approaches to Investigating UX
  • Quantum Computation
  • Research Methods in Computer Science
  • Cloud based Data Analysis
  • Game Design & Development in Real-Time Engines
  • Governance of Data Science
  • Group Project (Integrated Masters)
  • Cryptography Theory and Practice
  • Embedded Systems Design and Implementation
  • Engineering 2: Automated Software Engineering
  • Ethical Hacking, Analysis and Investigation
  • High-Integrity Systems Engineering
  • High-Performance Parallel and Distributed Systems
  • Human Factors: Technology in Context
  • Network Security
  • Player Experiences in Digital Games
  • Qualitative Approaches to Investigating UX
  • Quantum Computation
  • Research Methods in Computer Science