BSc (Econ)(Hons) Economics, Finance and Management
Spanning three years, with options to extend to four or five years to include a year ab...
MSc Machine Learning for Visual Data Analytics
Mile End
INTAKE: September
Program Overview
The MSc in Machine Learning for Visual Data Analytics at Queen Mary University of London is designed to offer a rigorous, interdisciplinary education combining machine learning, artificial intelligence, and computer vision. Students will gain an in-depth understanding of how to apply machine learning techniques to solve complex problems related to visual data, such as image recognition, object detection, video analysis, and visual pattern recognition. This program is ideal for students with a background in computer science, engineering, or related fields who wish to specialize in machine learning and its applications to visual data analytics. The program emphasizes hands-on learning and practical experience, equipping students with the skills necessary to tackle real-world challenges and advance the field of visual data analysis. Students will also have opportunities to engage with faculty members and researchers who are experts in artificial intelligence and machine learning, benefiting from their expertise and cutting-edge research projects.
Curriculum: The curriculum for the MSc Machine Learning for Visual Data Analytics at QMUL is structured to provide students with both theoretical foundations and practical skills. Core modules cover key areas of machine learning, including supervised and unsupervised learning, deep learning, neural networks, and reinforcement learning. Specialized modules focus on the application of machine learning to visual data, with courses in computer vision, image processing, pattern recognition, and visual data analytics. Students will also gain expertise in the use of popular machine learning frameworks and programming languages, including Python, TensorFlow, and PyTorch. In addition to the taught modules, students will undertake a major research project or dissertation, which allows them to apply their knowledge to a real-world problem in machine learning and visual data analytics. The curriculum also emphasizes the importance of understanding the ethical implications of using machine learning algorithms, particularly in the context of visual data, ensuring that students are well-equipped to consider the social and ethical challenges of their work.
Research Focus: The MSc in Machine Learning for Visual Data Analytics at Queen Mary University of London places a strong emphasis on research, with students encouraged to explore innovative solutions to pressing challenges in the field of visual data analytics. Research topics within the program include computer vision, deep learning for image and video analysis, facial recognition, autonomous systems, augmented reality, and medical image analysis. Queen Mary is known for its world-class research in artificial intelligence, machine learning, and computer vision, and students have the opportunity to collaborate with faculty members who are leading experts in these fields. The program offers students the chance to engage with cutting-edge research projects and contribute to advancing knowledge in machine learning for visual data analytics. This research-driven approach prepares students to pursue careers in academia or research-intensive industries, where they can continue to push the boundaries of what is possible with machine learning and visual data.
Industry Engagement: Industry engagement is a key aspect of the MSc Machine Learning for Visual Data Analytics program at Queen Mary University of London. The university maintains strong links with leading companies and organizations in sectors such as technology, healthcare, automotive, and entertainment, providing students with opportunities to work on industry-sponsored projects, internships, and collaborations. Through these industry partnerships, students gain practical experience in applying machine learning and visual data analytics to real-world problems, from developing computer vision systems to creating AI-driven solutions for healthcare diagnostics. The program’s strong emphasis on industry collaboration ensures that students graduate with the skills and experience necessary to make an immediate impact in the workforce. Additionally, students benefit from access to a network of professionals, guest speakers, and industry events, which help them build valuable connections and explore potential career opportunities in the growing field of machine learning.
Global Perspective: The MSc in Machine Learning for Visual Data Analytics at Queen Mary University of London incorporates a global perspective on machine learning and visual data analysis. The program is designed to expose students to the international scope of the field, with research, case studies, and applications that span a wide range of global challenges and industries. The use of machine learning for visual data analytics has worldwide implications, from improving healthcare outcomes through medical image analysis to enhancing security with facial recognition technology. Students in the program will engage with global research and trends in AI and machine learning, exploring issues such as data privacy, ethics, and the societal impact of AI technologies. Queen Mary University of London’s international research collaborations and global academic partnerships provide students with a unique opportunity to participate in global projects and gain exposure to diverse perspectives on the challenges and opportunities in machine learning and visual data analytics.
Location
Mile End
Score
IELTS 6.5
Tuition Fee
£ 29950
Postgraduate Entry Requirements:
- Applicants should have successfully completed a bachelor's degree or its equivalent from a recognized institution with a minimum overall score of 60% or equivalent.
- English language proficiency is required, and applicants must provide evidence of their English language skills through an approved language test.
- IELTS: A minimum overall score of 6.5 with no individual component below 6.0.
- TOEFL: A minimum overall score of 92, with at least with at least 17 in Listening, 18 in Reading, 20 in Speaking, and 21 in Writing.
- PTE Academic: A minimum overall score of 71 with 65 in Writing, and 59 in Reading, Listening and Speaking..
- Some postgraduate programs may have specific subject prerequisites or additional requirements.
Students must provide:
- academic marksheets & transcripts
- letters of recommendation
- a personal statement - SOP
- passport
- other supporting documents as required by the university.
Work experience: Some postgraduate courses may require relevant work experience in the field.
It is important to note that meeting the minimum entry requirements does not guarantee admission, as the university considers factors such as availability of places and competition for the program. Additionally, some courses may have higher entry requirements or additional selection criteria, such as interviews or portfolio submissions.
Queen Mary University of London offers a range of scholarships and bursaries to its students.
Queen Mary International Excellence Scholarships: A scholarship program for international undergraduate and postgraduate students who have an offer of admission from Queen Mary University of London and have demonstrated academic excellence. The scholarship covers full tuition fees for one year of study.
Queen Mary Law Scholarships: A scholarship program for undergraduate and postgraduate law students who have an offer of admission from Queen Mary University of London and have demonstrated academic excellence. The scholarship covers full or partial tuition fees, depending on the level of academic achievement.
Queen Mary Engineering and Materials Science Scholarships: A scholarship program for undergraduate and postgraduate students studying engineering or materials science who have an offer of admission from Queen Mary University of London and have demonstrated academic excellence. The scholarship covers full or partial tuition fees, depending on the level of academic achievement.
Graduates of the MSc in Machine Learning for Visual Data Analytics program from Queen Mary University are poised for diverse and impactful career opportunities.
Machine Learning Engineer: Graduates can work as machine learning engineers, designing and implementing AI algorithms for visual data analysis in industries such as healthcare, finance, and entertainment.
Computer Vision Specialist: Graduates may pursue roles in computer vision, developing technologies for image recognition, object tracking, and augmented reality applications.
Data Scientist: Graduates can leverage their expertise in visual data analytics to work as data scientists, uncovering insights from complex datasets and driving data-informed decision-making.
AI Researcher: Graduates interested in research can contribute to cutting-edge AI research, advancing the field through innovative machine learning models and techniques.
Natural Language Processing Engineer: Graduates with NLP skills can explore roles in natural language processing, creating chatbots, language translation systems, and sentiment analysis tools.
AI Consultant: Graduates may offer consultancy services, assisting organizations in integrating AI and machine learning solutions into their operations.
Start-up Entrepreneur: Graduates with a passion for innovation can establish AI-focused start-ups, developing novel applications and solutions for visual data analytics.
Academic Pursuits: Graduates can pursue further academic studies or research positions, contributing to the academic discourse and pushing the boundaries of AI knowledge.
Healthcare and Biomedical Analysis: Graduates can contribute to healthcare and biomedical fields, utilizing AI to analyze medical images, diagnose diseases, and enhance patient care.
Financial Analysis and Trading: Graduates can apply machine learning to financial data, working in quantitative analysis, algorithmic trading, and risk assessment.
