MSc Finance
The MSc Finance course at the University of Plymouth in the UK offers a comprehensive a...
Plymouth
INTAKE: September
The MSc in Artificial Intelligence at the University of Plymouth covers a wide range of topics related to AI, machine learning, data science, and robotics. The program combines theoretical foundations with practical applications to provide students with a comprehensive understanding of AI technologies.
Foundations of AI: Students are introduced to the fundamental concepts and theories of AI, including intelligent agents, knowledge representation, reasoning, and problem-solving. They gain a solid understanding of the theoretical underpinnings of AI and its applications in various domains.
Machine Learning: The program covers the principles and techniques of machine learning, including supervised and unsupervised learning, deep learning, and reinforcement learning. Students learn how to train and evaluate machine learning models using real-world datasets.
Data Mining and Big Data Analytics: Students learn how to extract useful insights from large datasets through data mining and big data analytics techniques. They explore data preprocessing, feature extraction, pattern recognition, and data visualization to uncover meaningful patterns and trends.
Natural Language Processing: The program introduces students to natural language processing (NLP) techniques, enabling them to build AI systems that can understand and process human language. Students learn about language modeling, sentiment analysis, text classification, and machine translation.
Computer Vision: Students gain knowledge in computer vision, which involves processing and analyzing visual data. They learn about image recognition, object detection, image segmentation, and video analysis techniques using AI algorithms.
Robotics and Autonomous Systems: The program explores the integration of AI with robotics and autonomous systems. Students learn about robot perception, motion planning, control, and human-robot interaction, preparing them for careers in robotics and automation.
Ethical and Legal Considerations: Students are exposed to the ethical and legal aspects of AI, including privacy, bias, transparency, and accountability. They learn how to design and deploy AI systems that adhere to ethical guidelines and legal frameworks.
AI Applications: The program provides practical exposure to real-world AI applications across various domains, such as healthcare, finance, cybersecurity, and marketing. Students have the opportunity to work on AI projects, applying their knowledge to solve specific challenges.
Research Methods in AI: Students develop research skills in AI, including experimental design, data collection, and statistical analysis. They learn how to conduct independent research and contribute to the advancement of AI knowledge.
Dissertation: The program includes a dissertation project where students work on an AI research topic of their choice. They apply their knowledge and skills to investigate a specific problem, propose innovative solutions, and present their findings in a comprehensive report.
Plymouth
IELTS 6.5
£ 16700
Postgraduate Entry Requirements:
Students must provide:
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.
The University of Plymouth offers various scholarships and financial support options to help students fund their studies.
Graduates of the MSc in Artificial Intelligence from the University of Plymouth have excellent career prospects in the rapidly growing field of AI.
AI Engineer/Developer: Graduates can work as AI engineers or developers, designing and developing AI algorithms, models, and systems. They can contribute to the development of AI applications, such as virtual assistants, recommendation systems, and predictive analytics tools.
Machine Learning Engineer: Graduates can pursue careers as machine learning engineers, specializing in the development and deployment of machine learning models. They can work on projects involving data analysis, model training, and optimization.
Data Scientist: Graduates can work as data scientists, leveraging AI techniques to extract insights from large datasets. They can apply their skills in data preprocessing, feature engineering, and predictive modeling to solve complex business problems.
AI Researcher: Graduates can pursue research-oriented careers as AI researchers, working in academic institutions, research labs, or industry research and development departments. They can contribute to the advancement of AI knowledge through innovative research projects.
AI Consultant: Graduates can work as AI consultants, providing expertise and guidance to organizations seeking to implement AI technologies. They can offer strategic advice, develop AI strategies, and assist in the implementation and optimization of AI systems.
Robotics Engineer: Graduates with a focus on robotics and autonomous systems can work as robotics engineers, designing and developing intelligent robots and automation systems. They can contribute to advancements in areas such as industrial automation, healthcare robotics, and autonomous vehicles.
AI Ethics and Policy Specialist: Graduates can work in the ethical and policy aspects of AI, ensuring responsible and ethical deployment of AI technologies. They can provide guidance on issues such as bias, fairness, privacy, and transparency in AI systems.
AI Entrepreneur: Graduates with an entrepreneurial mindset can start their own AI-focused ventures, developing AI-based products or services. They can identify market opportunities, innovate AI solutions, and build their own AI startups.
AI Project Manager: Graduates can work as AI project managers, leading and overseeing AI projects within organizations. They can manage project timelines, budgets, and resources while ensuring successful delivery of AI initiatives.
AI Specialist in Specific Domains: Graduates can specializeas AI specialists in specific domains such as healthcare, finance, cybersecurity, marketing, or agriculture. They can apply their AI knowledge and skills to address industry-specific challenges and drive innovation in their respective fields.