Artificial Intelligence and Data Engineering MSc

1 Year On Campus Masters Program

University College London

Program Overview

The MSc in Artificial Intelligence and Data Engineering at UCL is a one-year programme combining software engineering, data engineering, and machine learning to train students in building scalable AI-driven systems. It suits students with strong computational or mathematical backgrounds who want to design and deploy data-intensive intelligent systems.

Curriculum structure

Year of Study (one-year full-time):
Students begin with Requirements Engineering and Software Architecture, Engineering for Data Analysis 1, and Software Development Practice, learning to design robust software systems and manage analytical data workflows. They then progress to modules such as Engineering for Data Analysis 2 and Validation and Verification, gaining skills in constructing full data pipelines, ensuring system reliability, and integrating machine learning into engineered solutions.
The year concludes with the MSc Project, where students develop an AI or data-engineering system that demonstrates end-to-end design, implementation, and evaluation.

Focus areas (string):
Software engineering; data engineering; machine learning; scalable data systems; AI deployment.

Learning outcomes (string):
Ability to design large-scale data systems; build and validate AI applications; manage data pipelines; integrate ML into software solutions; complete independent engineering projects.

Professional alignment (accreditation):
Prepares graduates for roles such as AI engineer, ML engineer, data engineer, and software architect in tech and data-driven industries.

Reputation (employability rankings):
UCL ranks among the top global universities with a highly regarded Computer Science department and strong employability outcomes in engineering and AI sectors.

Experiential Learning (Research, Projects, Internships etc.)

Students gain practical skills through project-based learning, using UCL's high-performance computing facilities and working with real-world datasets from industry and research partners. The programme emphasizes implementing machine learning systems and data science pipelines in Python, with access to specialized computing resources like the Myriad High Performance Computing facility. This applied learning is structured around several key components:

Core Software & Programming: Intensive use of Python and its core data science libraries (e.g., NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch), with potential use of Spark for large-scale data processing.
Computing Facilities: Access to UCL's Myriad High Performance Computing cluster and the Department of Computer Science's computing labs for demanding computational tasks.
Group Projects: A significant team-based software engineering project focused on building a complete, scalable data science and machine learning system.
Research Dissertation: An individual research project (MSc thesis) often linked to ongoing research within UCL's Centre for Artificial Intelligence or with external industrial partners.
Digital Tools & Platforms: Use of cloud platforms and version control systems like Git for collaborative software development and model deployment.

Progression & Future Opportunities

Graduates of UCL’s MSc in Artificial Intelligence and Data Engineering leave with practical skills in machine learning, software engineering for large data systems, and scalable data‑pipeline design, making them attractive to employers building production AI systems. The programme’s industry projects and UCL’s reputation lead to rapid entry into technical roles across tech, finance and research organisations. Many alumni move into applied engineering or research positions within months of graduating.

Typical job roles: AI Software Engineer, Machine Learning Engineer, Data Engineer, MLOps Engineer.

Careers support: UCL Careers provides tailored workshops, employer events, CV/interview coaching and alumni networking; the department also connects students to industry projects via the IXN Industry Exchange Network for employer engagement and recruitment.
Employment stats & salary figures: UCL postgraduate computing graduates report strong employment outcomes and competitive starting salaries in data/AI roles (industry reports place many London-based graduate starting salaries in the £40k–£60k range depending on role and employer).
University–industry partnerships: formal industry collaborations and project placement opportunities are delivered through the IXN network and links with major tech employers who sponsor final projects and engage with the programme.
Long‑term accreditation value: the degree combines modules from established UCL software‑systems and machine‑learning programmes, giving durable signalling value for engineering and research roles at large tech firms and research centres.
Graduation outcomes: graduates are prepared to design, build and deploy production AI systems, enter MLOps/data‑platform teams, or continue into doctoral study; many secure roles where they lead development of scalable AI pipelines and data‑intensive applications.

Further Academic Progression: Graduates can pursue PhD or MPhil research in software engineering for data‑intensive systems, machine learning, or applied AI at UCL or other research universities, using the MSc project as a foundation for doctoral proposals and potential publications.