our msc data science and ai provides the opportunity to deepen your core competencies in data science and ai, and to strengthen your skills in developing data- and ai-driven products and services. the course actively explores the ethical and social dimensions of data science and ai —ensuring you have a deep and critical understanding of the impacts of related technologies, and a familiarity with arts and human-centred methods for designing and reasoning about new systems. using computer programming combined with arts and humanities critical approaches, you will apply scientific and mathematical principles to guide the creation and evaluation of mathematical models of real-world problems. this enables the creation of tools that take into account the computational and technical, but also the human, social and cultural aspects that emerge from the entanglement of humans, technology and the environment. you will apply data science and ai to a broad range of domains, involving diverse types of data and content, from numerical data to text and media. and you will critically engage with contemporary thinkers from diverse disciplines concerned with the ethical and social implications of data science and ai. you will approach through collaborative, creative problem solving which leverages and strengthens your technical and teamwork skills, critical thinking, and your knowledge of application domains and stakeholders. your thesis project should target your preferred technology sector or domain of work, supporting your progression to industry or further academic research. we are committed to ensuring that your skills are set within an ethical framework and are working to embed ual’s principles for climate, social and racial justice. what to expect technical skills for data science and ai: learn advanced coding, data science and ai skills that make use of key modern programming languages and technical frameworks, which can be applied in a wide range of data science and ai industries and beyond. human and arts-centred approaches: learn and apply methodologies coming from humanities and the arts that will provide critical and out-of-the-box approaches to your data science and ai practice. project-based learning: complete a range of data science and ai projects, applying your skills and knowledge to real-world problems. frequent and regular hands-on learning activities give you time to practice new skills while receiving rich feedback. ethical data and ai practices: learn how data and ai practices have the potential to impact individuals and society, and you will learn about techniques for human-centred design and critique of data and ai systems. collaboration and creativity: collaborate with your postgraduate peers to creatively solve problems together, bringing your varied undergraduate, professional, and personal experiences to advanced problems. these abilities and attributes are sought after by many graduate employers. the cci community: join a significant community of students, academics and researchers who are passionate about the future of computing. you will learn alongside msc students on our other postgraduate courses. you will also be part of our integrated online community where you can access technical support, events, employment opportunities and more. a supportive environment: you will have access to both technical and pastoral support and be part of a community committed to promoting accessibility, diversity and inclusion.  industry experience and opportunities you will learn using industry standard tools and advanced frameworks ensuring you are ready to progress to a wide range of roles in data science and ai, across the technology sector and beyond. you will benefit from a wide range of cross-institute talks and will meet industry representatives throughout your studies. entrepreneurship is encouraged and the opportunity to start enterprises will be supported with business training and access to incubator programs, as well as through team entrepreneurship pedagogies. mode of study msc data science and ai is offered in full-time mode and runs for 45 weeks over 12 months. you will be expected to commit an average of 40 hours per week to your course, including teaching hours and independent study.