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The MSc Advanced Machine Learning at University of Bath delivers deep training in mathematical foundations, machine-learning theory, and cutting-edge ML techniques, preparing students for research or high-skilled industry roles. It suits graduates with a strong quantitative background (e.g., computer science, mathematics, engineering) who want to specialise in ML, AI, and data-driven systems.
Curriculum structure
In the taught phase, students cover Foundational Machine Learning, where core algorithms rooted in probability, linear algebra and statistics provide a rigorous base. They also study Understanding Deep Learning to learn neural networks, convolutional and transformer models, and Applied Machine Learning, applying ML pipelines to real datasets using current tools and libraries. Other modules like Bayesian Machine Learning, Computer Vision, Natural Language Processing, and Frontiers of Machine Learning let students explore specialised domains, probabilistic inference, image and language tasks, and state-of-the-art ML research. The programme culminates in a Specialist Project (Dissertation), where students conduct independent research or build an ML system, synthesising theory, practice and evaluation.
Focus areas :
“Machine learning theory, deep learning, Bayesian inference, computer vision, NLP, applied ML systems, independent ML research”
Learning outcomes:
“Develop and apply advanced ML & deep-learning methods; design and implement ML systems; perform computer vision and NLP tasks; conduct independent ML research; evaluate and deploy data-driven models responsibly.”
Professional alignment (accreditation):
The degree is aligned with industry demand for ML engineers, data-scientists, AI researchers and developers of intelligent systems — offering skills sought by tech companies, research institutions and data-driven industries.
Reputation (employability):
University of Bath is well-regarded in the UK for STEM and data-science programmes; this MSc’s focus on rigorous ML foundations, practical skills and research readiness gives graduates strong employability and good preparation for PhD or industry-level ML/AI roles.
Students gain practical skills through hands-on projects using the University's high-performance computing infrastructure, applying AI and machine learning techniques to solve complex, real-world problems. The programme emphasizes both theoretical understanding and practical implementation, with a strong focus on software development and system building for AI applications. This applied learning is structured around several key components:
Core Software & Programming: Intensive use of Python as the primary language, with deep exposure to key AI and machine learning libraries including TensorFlow, PyTorch, and Scikit-learn.
Computing Facilities: Access to the University's High-Performance Computing (HPC) resources, including the Balena HPC service, for training complex models and handling large datasets.
Research Project: A substantial individual research dissertation (MSc project) that allows students to pursue a specialist area, often involving the development of a novel AI application or algorithm.
Group Projects: Team-based software engineering projects focused on designing and building complete AI systems to address specific challenges.
Digital Tools & Platforms: Use of industry-standard tools for version control (e.g., Git) and collaborative development.
Graduates of the MSc Advanced Machine Learning at University of Bath are equipped for roles such as machine learning engineer, AI researcher, data scientist, and robotics specialist:
The Careers Service offers CV and interview workshops, plus employer networking focusing on AI careers.
Graduates are highly employable in healthcare, finance, autonomous vehicles; typical salaries range £40,000–£60,000.
Partnerships with industry and research centres provide opportunities for practical projects and placements.
The course delivers deep expertise in computer vision, reinforcement learning, and AI system deployment.
Graduates complete significant research projects demonstrating advanced applied skills.
Further Academic Progression: Graduates may pursue PhDs in machine learning or AI to advance in research or industry leadership.
You should have a Bachelor’s honours degree or international equivalent, typically a high 2:2 or above.India- Typically, you should have a Bachelor degree with a final overall result of at least First Class.USA- You should have an Honors Bachelor degree or Bachelor degree with a final overall result of at least CGPA 3.0 on a 4-point scale.IELTS: 6.5 overall with no less than 6.0 in all componentsTOEFL IBT: 90 overall with a minimum 21 in all 4 componentsMachine Learning EngineerAI Software DeveloperData ScientistResearch ScientistAI ConsultantNatural Language Processing EngineerComputer Vision EngineerRobotics Software EngineerAlgorithm DeveloperPhD ResearcherQuantitative AnalystBusiness Intelligence Specialist
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