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1 Year On Campus Masters Program
University College LondonThe MSc Artificial Intelligence and Data Engineering at UCL is an innovative, STEM-designated postgraduate program designed to equip students with the technical expertise to design, build, and optimize systems that combine AI with large-scale data engineering. Offered by the Department of Electronic and Electrical Engineering, the program integrates machine learning, data processing architectures, and scalable systems to address the growing demand for professionals capable of developing intelligent, data-driven technologies.
This interdisciplinary program prepares students to lead in domains ranging from smart systems and robotics to finance, healthtech, and autonomous infrastructure, blending theoretical knowledge with hands-on engineering and computational skills.
Program Format & Duration
Full-time, on-campus (London, UK)
Duration: 1 year (12 months)
Start Date: September
Award: MSc Artificial Intelligence and Data Engineering
Faculty: Engineering Sciences
Core Curriculum Components
The program focuses on developing advanced competencies in AI models, data architecture, and real-time processing systems, supported by rigorous computational and mathematical training.
Core Modules
Artificial Intelligence Foundations
Fundamentals of Machine Learning
Deep Learning and Neural Networks
Computer Vision and Natural Language Processing
AI for Decision Making
Data Engineering & Scalable Systems
Cloud Computing for Big Data
Real-Time Data Processing
Distributed Systems and High-Performance Computing
Software Engineering for Data-Intensive Applications
Programming & Tools
Python, TensorFlow, PyTorch
Spark, Hadoop, and cloud platforms (AWS, Azure, or GCP)
Containerization and deployment using Docker/Kubernetes
Optional Electives (Sample Options)
Robotics and Autonomous Systems
Cybersecurity for AI Systems
Data Ethics and Responsible AI
Human-Computer Interaction
Financial or Biomedical AI Applications
Research Project / Dissertation
A substantial individual research project conducted over the summer term
Supervised by UCL faculty, often aligned with real-world data and AI system challenges
May involve collaborations with research centers or industry partners
UCL emphasizes practical application, project-based learning, and interdisciplinary engagement, making the program deeply immersive and professionally relevant.
Individual Research Project
Central to the program and an opportunity for students to specialize in an area of interest
Projects often involve real datasets and advanced AI methodologies
Assessment includes a dissertation and oral presentation
Project-Based Coursework
Lab-based modules and team projects simulate real engineering problems
Emphasis on deployment, performance, and scalability of AI systems
Opportunities to engage in competitions, design challenges, and hackathons
Industry Engagement
UCL’s strong ties to London’s AI and fintech ecosystem offer access to networking events, company-led workshops, and guest lectures
Opportunities to engage with startups, multinational tech companies, and research labs
Graduates from this MSc program are trained to work at the intersection of AI innovation and system-level engineering, making them well-suited for technical, strategic, and R&D roles.
Career Outcomes
Typical roles include:
AI Engineer
Machine Learning Engineer
Data Engineer / Big Data Architect
Cloud Solutions Architect
Robotics or Autonomous Systems Developer
AI Product Manager
Top Employers
Graduates are prepared for careers at:
Google DeepMind, Microsoft, Meta, Amazon
Accenture, Palantir, Thoughtworks
Financial and consulting firms leveraging AI solutions
Startups in robotics, AI healthcare, or edge computing
Government or public sector AI innovation labs
Further Study
Graduates may pursue:
PhDs in AI, Robotics, or Computational Engineering
Research fellowships at institutions like The Alan Turing Institute
Advanced training in responsible AI, ethics, or systems engineering
Academic Degree: Hold a UK upper second-class honours degree (2:1) or international equivalent in computer science, computing, or software engineering with strong background in data systems, AI, and mathematics. Relevant Experience: Relevant work experience in AI or software engineering may be considered in lieu of academic background.English Proficiency: Meet UCL Level 2 English language standards (TOEFL/iBT, IELTS, etc.) as specified on university guidelines.Transcripts & References: Provide full academic transcripts and referee contact information via the online portal, with certified originals only required upon admission.Personal Statement: Submit a personal statement outlining your interest, relevant background, and suitability for the programme. (Implied, though not explicitly stated in search snippets—common for UCL Engineering applications.)Application Fee & Deadline: Pay the standard application fee (typically £80) and apply before the programme's specified deadline (usually in early July for September entry). (Fee/deadline implied; not detailed in search)Eligible for UCL-wide scholarships such as Global MSc scholarships (~£15,000) and engineering department awardsAdditional funding via fellowships like Graduate Research Scholarships, Research Excellence Scholarships, Commonwealth, Chevening, etc. (varies by program year) Data Engineer Machine Learning Engineer AI Solutions Engineer Cloud Data Engineer / Cloud Architect DevOps Engineer (with AI focus) Data Platform Engineer AI Product Manager Digital Transformation Consultant ETL/ELT Developer Big Data Analyst ata Governance or MLOps Engineer BI Developer / Data Visualization Specialist 
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