Artificial Intelligence (BEng)
Course Overview
This course equips you with the cutting-edge skills to design and develop the next generation of intelligent systems. You will master the core principles of AI and machine learning, graduating with a highly sought-after skillset to drive innovation across countless industries. The program combines rigorous theoretical learning with hands-on, practical application in modern lab facilities.
Key Program Highlights
- Master core AI technologies including deep learning, computer vision, and data analytics
- Gain practical, research-led experience in modern computing labs
- Build systems capable of making intelligent decisions and actions
- Tailor your expertise through a range of specialist optional modules
- Undertake a significant individual research project in your final year
Course Overview
This course equips you with the cutting-edge skills to design and develop the next generation of intelligent systems. You will master the core principles of AI and machine learning, graduating with a highly sought-after skillset to drive innovation across countless industries. The program combines rigorous theoretical learning with hands-on, practical application in modern lab facilities.
Key Program Highlights
- Master core AI technologies including deep learning, computer vision, and data analytics
- Gain practical, research-led experience in modern computing labs
- Build systems capable of making intelligent decisions and actions
- Tailor your expertise through a range of specialist optional modules
- Undertake a significant individual research project in your final year
Requirements
Modules
- AICE Lab Programme Year 1
- Algorithms and Analysis
- Data Analytics
- Digital Computer Systems
- Ethics and Security of Computing
- High-Level Programming
- Low-Level Programming
- Mathematics for Artificial Intelligence and Computer Engineering (I)
- Mathematics for Artificial Intelligence and Computer Engineering (II)
- AI and CE Interdisciplinary Group Project
- Artificial Intelligence and Learning Machines
- Code Transformation
- Digital Signal Processing
- Machine Learning (I)
- Parallel and Distributed Computing
- Scientific Computing
- Systematic Design
- Machine Learning (II)
- Part III Individual Project Phase 1
- Part III Individual Project Phase 2
- Advanced Computer Networks
- Advanced Databases
- Causal Reasoning and Machine Learning
- Computational Biology
- Computer Vision
- From Data to Dynamical Model: System Identification
- Green Electronics
- High Performance Computing
- Natural Language Processing
- Parallel Programming
- Real-Time Computing and Embedded Systems
- Robotic Systems
- Security of Cyber Physical Systems
