BSc Hons Accounting and Management
Queen Mary University of London's BSc-Hons- Accounting and Management program ...
MSc Big Data Science
Mile End
INTAKE: September
Program Overview
The MSc Big Data Science program at Queen Mary is at the forefront of the data revolution, preparing students to become proficient data scientists. The program covers a wide range of topics.
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Data Mining and Machine Learning: Students gain insights into advanced data mining techniques and machine learning algorithms to extract valuable knowledge from vast datasets.
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Big Data Analytics: The program focuses on the tools and techniques used to analyze and interpret big data, enabling students to draw meaningful conclusions from complex datasets.
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Data Visualization: Students learn how to present and communicate data effectively through visualizations, making complex information accessible to a wide audience.
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Distributed Computing: The program introduces students to distributed computing frameworks like Apache Hadoop and Spark, vital for processing massive datasets.
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Data Privacy and Ethics: Students explore the ethical considerations surrounding big data, ensuring responsible and secure handling of sensitive information.
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Data Science Project: As part of the program, students undertake a data science project, applying their skills to solve real-world problems and gain practical experience.
Location
Mile End
Score
IELTS 6.5
Tuition Fee
£ 28950
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 Big Data Science program have exciting career opportunities in diverse sectors.
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Data Scientist: Graduates can work as data scientists, applying their skills to analyze and interpret data for informed decision-making.
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Big Data Analyst: Graduates may pursue roles as big data analysts, responsible for extracting valuable insights from large datasets.
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Data Engineer: Graduates can become data engineers, developing and maintaining data infrastructure and pipelines.
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Business Intelligence Analyst: Graduates with expertise in big data can work as business intelligence analysts, helping businesses make strategic decisions based on data-driven insights.
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Data Consultant: Graduates may work as data consultants, providing expertise and solutions to organizations seeking to leverage their data.
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Research Scientist: Graduates can embark on research careers, exploring new methods and techniques in the field of big data science.
