MSc Accounting and financial Management
The MSc Accounting and Financial Management course at Royal Holloway University of Lond...
MSc Machine Learning
Egham Campus
INTAKE: September
Program Overview
The MSc Machine Learning course at Royal Holloway, University of London offers students a comprehensive understanding of the principles and applications of machine learning. This program combines theoretical knowledge with practical skills to prepare students for careers in industries such as technology, finance, healthcare, and more.
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Fundamentals of Machine Learning: Students are introduced to the fundamental concepts and techniques of machine learning. They learn about various algorithms, including supervised learning, unsupervised learning, reinforcement learning, and deep learning.
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Statistical Methods for Machine Learning: The course covers statistical methods that underpin machine learning algorithms. Students learn about probability theory, statistical inference, regression analysis, and hypothesis testing, enabling them to make informed decisions and analyze data effectively.
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Data Preprocessing and Feature Engineering: Students learn how to preprocess and transform data to make it suitable for machine learning algorithms. They explore techniques such as data cleaning, feature scaling, dimensionality reduction, and handling missing data.
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Machine Learning Algorithms: The program provides in-depth knowledge of a wide range of machine learning algorithms. Students study linear models, decision trees, support vector machines, neural networks, clustering algorithms, and ensemble methods.
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Deep Learning and Neural Networks: Students delve into the field of deep learning, focusing on neural networks and their applications. They learn about convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and natural language processing (NLP) techniques.
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Big Data Analytics: The course addresses the challenges and opportunities associated with big data. Students learn how to handle large datasets, use distributed computing frameworks such as Hadoop and Spark, and apply machine learning techniques to extract meaningful insights from big data.
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Advanced Topics in Machine Learning: Students have the opportunity to explore advanced topics in machine learning based on their interests. These may include topics such as reinforcement learning, time series analysis, transfer learning, or Bayesian machine learning.
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Machine Learning Tools and Libraries: Students gain practical experience with popular machine learning tools and libraries, such as Python, TensorFlow, scikit-learn, and Keras. They learn how to implement machine learning algorithms, perform model evaluation, and build predictive models.
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Ethical and Legal Considerations: The program addresses the ethical and legal implications of machine learning. Students examine topics such as bias in algorithms, privacy concerns, transparency, and responsible AI development.
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Research and Dissertation: As part of the program, students undertake a research project or dissertation. They have the opportunity to apply their knowledge and skills to a real-world problem or conduct research in a specific area of machine learning.
Location
Egham Campus
Score
IELTS: 6.5
Tuition Fee
£ 22000
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% to 65% 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.
- PTE Academic: A minimum overall score of 61 with no individual score below 54.
- 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.
Royal Holloway, University of London offers a range of scholarships to support students in their academic pursuits. These scholarships are designed to recognize excellence and provide financial assistance to eligible students.
- Founder's Scholarship: This is the most prestigious scholarship at Royal Holloway, awarded to undergraduate students who demonstrate exceptional academic achievement and potential. It covers full tuition fees and provides a generous annual stipend.
- Royal Holloway Excellence Scholarship: This scholarship is awarded to undergraduate students based on their academic achievement and potential. It offers a £2,500 tuition fee waiver for each year of study.
- International Excellence Scholarship: This scholarship is specifically for international undergraduate students. It provides a tuition fee reduction of £4,000 per year for the duration of the program.
- Masters Scholarships: Royal Holloway offers a variety of scholarships for postgraduate students, including the RHUL Principal's Masters Scholarship, the RHUL International Excellence Masters Scholarship, and subject-specific scholarships.
- Sports Scholarships: These scholarships are available to students who excel in sports and have the potential to represent the university at a high level. They provide support in the form of financial assistance and access to training facilities.
It's important to note that scholarship availability, eligibility criteria, and application deadlines may vary.
The MSc Machine Learning program opens up a range of career prospects in industries where machine learning and data analysis are in high demand.
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Data Scientist: Graduates can work as data scientists, using machine learning techniques to extract insights from large datasets, develop predictive models, and drive data-informed decision-making.
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Machine Learning Engineer: Graduates can pursue careers as machine learning engineers, focusing on the implementation and deployment of machine learning models, optimization of algorithms, and development of scalable solutions.
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AI Researcher: Graduates can work in research positions, contributing to advancements in machine learning and AI. They may work on developing new algorithms, improving existing models, or solving complex problems in specific domains.
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Data Analyst: Graduates can work as data analysts, utilizing their knowledge of machine learning to analyze data, identify patterns, and communicate findings to stakeholders.
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Consultant or Advisor: Graduates can work as consultants or advisors, providing expertise in machine learning and data analysis to businesses and organizations across various industries.
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AI Product Manager: Graduates can take on roles as AI product managers, responsible for overseeing the development and implementation of AI-powered products or services.
The MSc Machine Learning course at Royal Holloway, University of London equips students with the necessary skills and knowledge to excel in the rapidly growing field of machine learning and opens up diverse career opportunities in industries driven by data and AI.
