Curious about studying Artificial Intelligence and Data Engineering MScat UCL (University College London)? We've gathered all the key details—entry requirements, modules, fees, and more. Hear from real students by checking out reviews, or take the next step by booking an open day to explore it for yourself.
MSc - Master of Science
UCL (University College London) - Bloomsbury Campus
Full Time
Sep 2027
1 Year
Become an expert in Artificial Intelligence and Data Engineering with this one-year MSc. You'll gain advanced skills in software engineering, machine learning, and data engineering, preparing you to design, build, deploy, and manage AI systems in real-world environments. This MSc addresses the high demand for professionals with combined expertise in machine learning and software engineering. Integrating modules from our esteemed MSc in Software Systems Engineering and MSc in Machine Learning programmes, along with new data engineering modules, this programme equips you with the skills to excel as an AI Engineer, Machine Learning Engineer, or Data Engineer. You will learn the foundations and practices necessary for designing, coding, testing, deploying, and evolving large-scale, data-intensive systems. This programme culminates in a substantial engineering or research project, often conducted in collaboration with industry partners through our department’s leading Industry Exchange Network (IXN). This programme is ideal for you if you have a strong background and interest in software engineering and maths, and wish to specialise in the engineering of complex AI systems. If your primary interest is data science and machine learning, our other MSc programmes in AI and Machine Learning disciplines may be more suitable.
The module aims to teach students the background theoretical software engineering as it applies to commissioning cloud and parallel systems. Students will be taught applied, technical details of deploying and maintaining data science applications. Students will learn to develop and write their own large scale, state-of-the-art Machine Learning analyses.
The aims of the module are to provide a background in theoretical software engineering as it applies to large scale data analysis on parallel systems. Students will be introduced to principles in designing and developing data science applications platforms. The module will teach students the applied, technical details of deploying and building data science applications. By completion of the module students will be able to develop and write their own large scale, state-of-the-art Machine Learning analyses.
The module gives students experience in undertaking and completing a large project in software systems engineering encompassing the full software development lifecycle, applying techniques learned throughout the programme, including the technical skills of analysis, design and implementation.
This module aims to advance students' education in the professional skills and awareness (e.g., project management, professional ethics, teamwork, contemporary software practice) that they will need to undertake successful careers in software engineering.
The module will train students in the fundamental principles and latest techniques in systems requirements engineering and software architecture.
The module will train students in the principles, application, and analysis of software development practices. The module will cover the fundamental practices that one would expect from any software professional one would want to hire. It will also offer an introduction into research on analysing software and extracting information from software repositories. The module is based on decades of experience, including the latest thinking on software process and analysis.
The module will train students in the principles and techniques of validating and verifying software systems. The training will be intellectually demanding and will cover not only the state-of-the practice in validation and verification, but also the most significant trends, problems and results in validation and verification research.
A fee deposit will be charged at 2.5 percent of the first year fee.
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