BSc Hons Accounting and Management
Queen Mary University of London's BSc-Hons- Accounting and Management program ...
MSc Machine Learning for Visual Data Analytics
Mile End
INTAKE: September
Program Overview
The MSc in Machine Learning for Visual Data Analytics program at Queen Mary University is designed to equip students with advanced knowledge and practical skills in the realm of artificial intelligence, machine learning, and visual data analysis.
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Foundations of Machine Learning: Students delve into the fundamental concepts of machine learning, gaining insights into algorithms, statistical modeling, and data processing.
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Visual Data Analytics: The program focuses on techniques for analyzing and extracting insights from visual data, encompassing image and video analysis, computer vision, and pattern recognition.
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Deep Learning: Students explore deep learning methodologies, including neural networks, convolutional networks, and recurrent networks, for tasks such as image classification and object detection.
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Data Mining and Big Data: The curriculum covers data mining techniques and strategies for handling large-scale datasets, enabling students to extract meaningful patterns and knowledge.
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Feature Extraction and Dimensionality Reduction: Students learn methods for extracting relevant features from visual data and reducing dimensionality to enhance computational efficiency.
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Natural Language Processing (NLP): The program introduces NLP techniques for analyzing textual and linguistic data, enabling students to develop applications such as sentiment analysis and text summarization.
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Machine Learning Applications: Students explore real-world applications of machine learning, including healthcare diagnostics, autonomous vehicles, augmented reality, and more.
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Ethical and Social Implications: The curriculum addresses the ethical and societal considerations associated with machine learning and AI, fostering responsible and informed AI practitioners.
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Practical Projects: Students engage in hands-on projects, applying machine learning techniques to solve complex problems in visual data analytics.
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Industry Engagement: The program facilitates industry collaborations, guest lectures, and workshops to connect students with real-world applications and industry trends.
Location
Mile End
Score
IELTS 6.5
Tuition Fee
£ 26750
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.
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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.
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Computer Vision Specialist: Graduates may pursue roles in computer vision, developing technologies for image recognition, object tracking, and augmented reality applications.
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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.
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AI Researcher: Graduates interested in research can contribute to cutting-edge AI research, advancing the field through innovative machine learning models and techniques.
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Natural Language Processing Engineer: Graduates with NLP skills can explore roles in natural language processing, creating chatbots, language translation systems, and sentiment analysis tools.
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AI Consultant: Graduates may offer consultancy services, assisting organizations in integrating AI and machine learning solutions into their operations.
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Start-up Entrepreneur: Graduates with a passion for innovation can establish AI-focused start-ups, developing novel applications and solutions for visual data analytics.
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Academic Pursuits: Graduates can pursue further academic studies or research positions, contributing to the academic discourse and pushing the boundaries of AI knowledge.
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Healthcare and Biomedical Analysis: Graduates can contribute to healthcare and biomedical fields, utilizing AI to analyze medical images, diagnose diseases, and enhance patient care.
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Financial Analysis and Trading: Graduates can apply machine learning to financial data, working in quantitative analysis, algorithmic trading, and risk assessment.
